PRELIMINARY DESCRIPTION OF THE FUTURE AEROSPACE … · 2.3.1. Initial Scenario Formulation ......

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PRELIMINARY DESCRIPTION OF THE FUTURE AEROSPACE BUSINESS

ENVIRONMENT By

Johanna Bramham, Wathi Er, Richard Farr, Bart MacCarthy (University of Nottingham)

Ole-Jakob Dannemark (Volvo Aero Corporation)

Abstract: This document presents a preliminary description of approaches to model factors, themes, scenarios and value chains in the aerospace sector. Three key activities are described: (1) development of a detailed map of the factors that impact on the aerospace business environment and their inter-relationships; (2) an initial set of business scenarios and a preliminary tool for investigating future scenarios of most relevance - VIBES (VIVACE Interactive Business Environment Simulator); (3) a review of the System Dynamics scenario modelling approach and its application in the aerospace market. The report also outlines the next phase of the Business Environment research and the expected research outputs.

Dissemination: PU

Deliverable/Output n°: VIVACE 2.1/Unott/T/04002-0.1 Issue n°: 2

Keywords: Business environment, business factors, value chain, scenarios, modelling, systems dynamics

VIVACE Preliminary Description of the Future Aerospace Business Environment This document is classified as VIVACE Public



TABLE OF CONTENTS

0. EXECUTIVE SUMMARY ...................................................................................8

1. CHAPTER 1: INTRODUCTION TO THE RESEARCH....................................10 1.1. Introduction ..............................................................................................................10 1.2. Aims of the Research...............................................................................................10 1.3. Approach Selected...................................................................................................10 1.4. Report structure .......................................................................................................11

2. CHAPTER 2: INTRODUCTION TO BUSINESS ENVIRONMENT DEFINITION 12

2.1. Introduction ..............................................................................................................12 2.2. Existing business forecasting methods....................................................................12

2.2.1. Long-term Forecasting methods employed at Rolls-Royce ..............................12 2.3. Introduction to Scenario Analysis.............................................................................17

2.3.1. Initial Scenario Formulation ..............................................................................18 2.3.2. Scenario Construction Methodology.................................................................19

2.4. Use of Scenario Analysis within VIVACE.................................................................22 2.5. Conclusions .............................................................................................................22

3. CHAPTER 3: BUSINESS DRIVERS AND FACTORS ....................................24 3.1. Introduction ..............................................................................................................24 3.2. The Literature Survey Conducted ............................................................................24 3.3. Factors mapping of the future business environment ..............................................25 3.4. Detailed description of factors..................................................................................27

3.4.1. Passenger Traffic..............................................................................................27 3.4.2. Cargo (freight) traffic .........................................................................................29 3.4.3. Gross domestic product ....................................................................................30 3.4.4. Global trade ......................................................................................................31 3.4.5. The business cycle ...........................................................................................32 3.4.6. Exchange rates .................................................................................................33 3.4.7. Taxation ............................................................................................................34 3.4.8. Politics ..............................................................................................................35 3.4.9. Government subsidy .........................................................................................36 3.4.10. Safety ............................................................................................................37 3.4.11. Security .........................................................................................................38




3.4.12. Airport capacity..............................................................................................39 3.4.13. Environment ..................................................................................................40 3.4.14. Regulation .....................................................................................................42 3.4.15. Passenger attitudes ......................................................................................43 3.4.16. Demographics ...............................................................................................44 3.4.17. Green technology..........................................................................................45 3.4.18. Certification ...................................................................................................46 3.4.19. Operating costs .............................................................................................47 3.4.20. Cost of financial services ..............................................................................48 3.4.21. Cost of fuel ....................................................................................................49 3.4.22. Ticket price....................................................................................................50 3.4.23. Yield ..............................................................................................................51 3.4.24. Operator revenue ..........................................................................................52 3.4.25. Product and service offering..........................................................................53 3.4.26. Aircraft fleet ...................................................................................................53 3.4.27. Aircraft retirement..........................................................................................54 3.4.28. Demand for new aircraft ................................................................................55 3.4.29. Demand for maintenance..............................................................................56 3.4.30. Cost of maintenance .....................................................................................57 3.4.31. Air traffic management ..................................................................................58

3.5. Review Process for the Factors Maps .....................................................................59 3.5.1. Initial Feedback on the Factors Maps...............................................................60 3.5.2. Invitation for Further Feedback.........................................................................61

3.6. Conclusions .............................................................................................................61

4. CHAPTER 4: INITIAL FUTURE BUSINESS SCENARIOS.............................62 4.1. Introduction ..............................................................................................................62 4.2. Selection of Scenario Modelling Methodology .........................................................62 4.3. Initial Business Scenario Dimensions ......................................................................63

4.3.1. Hub Airports vs. Direct Flights ..........................................................................64 4.3.2. Aircraft age .......................................................................................................65 4.3.3. Operator Partnerships.......................................................................................66 4.3.4. Airport Availability .............................................................................................67 4.3.5. Quality of service ..............................................................................................68 4.3.6. Journey Length .................................................................................................69 4.3.7. War and Peace .................................................................................................70 4.3.8. Fuel Availability .................................................................................................71




4.3.9. Spare Parts Provision .......................................................................................73 4.3.10. East and West ...............................................................................................74 4.3.11. Environmental Issues ....................................................................................75 4.3.12. Space Activity................................................................................................76 4.3.13. Operator versus Manufacturer Power ...........................................................77 4.3.14. Private Aviation .............................................................................................79 4.3.15. Attitudes to Risk ............................................................................................80 4.3.16. Size of Payload .............................................................................................82 4.3.17. Aircraft Variety...............................................................................................83 4.3.18. Business Start-ups ........................................................................................84 4.3.19. Freight Activity...............................................................................................84

4.4. From Scenarios to Themes......................................................................................85 4.5. A Software Tool to Support Investigation of Anticipated Future Business Environments......................................................................................................................86 4.6. Invitation for Feedback on Business Scenarios .......................................................93 4.7. Conclusions .............................................................................................................93

5. CHAPTER 5: BUSINESS ENVIRONMENT MODELLING ..............................94 5.1. Introduction ..............................................................................................................94

5.1.1. Scope and aims of modelling............................................................................94 5.1.2. Application of the model ...................................................................................94 5.1.3. Approach to modelling ......................................................................................95

5.2. State of the art modelling methods for evaluating market behaviour and strategic responses ...........................................................................................................................96

5.2.1. Methods for strategy evaluation........................................................................96 5.2.2. Methods for evaluating market behaviour.........................................................97 5.2.3. Simulation methods for evaluating market behaviour and strategic responses 97 5.2.4. Using System Dynamics to Simulate Demand and Evaluate Policies ..............97 5.2.5. Demonstrations of Aerospace System Dynamics Models ..............................100 5.2.6. Using Simulation Tools and the Practicalities of Integrating Data ..................100

5.3. Existing models of the aerospace environment .....................................................101 5.3.1. Model for investigating aircraft ordering policies by Lufthansa .......................101 5.3.2. Model for predicting demand for a commercial jet manufacturer....................103 5.3.3. Evaluating the airline operator strategies – Southwest Airlines v People Express Airlines ............................................................................................................104 5.3.4. Conclusions on existing models .....................................................................105 5.3.5. Potential approaches in System Dynamics for Modelling of the Aerospace Market 105




5.4. Proposed modelling ...............................................................................................106 5.4.1. Problem definition ...........................................................................................106 5.4.2. System diagram..............................................................................................107 5.4.3. Definition of modelling variables .....................................................................107

5.5. Model development and use..................................................................................107 5.5.1. Modular build of the model..............................................................................107 5.5.2. Phases of testing and validation of the model ................................................108 5.5.3. Policies design................................................................................................108

5.6. Conclusions ...........................................................................................................110 5.6.1. Status on business environment modelling ....................................................111 5.6.2. Next steps in modelling...................................................................................111 5.6.3. An integrated effort .........................................................................................111 5.6.4. Business environment modelling within VIVACE............................................111

6. CHAPTER 6: FUTURE VALUE CHAIN DESCRIPTION ...............................113 6.1. Introduction ............................................................................................................113 6.2. Describing the value chain.....................................................................................113 6.3. Development of value chain analysis within VIVACE ............................................113 6.4. Conclusions on further work ..................................................................................117

7. CHAPTER 7: CONCLUSIONS......................................................................118 7.1. Introduction ............................................................................................................118 7.2. Summary of Business Environment Definition Activities........................................118 7.3. Further Work ..........................................................................................................121

LIST OF FIGURES

Figure 2.1: Sample aircraft capacity forecast 13 Figure 2.2: Available Seat Kilometres by aircraft size 13 Figure 2.3: Primary and secondary node breakdown 14 Figure 2.4: Sources of Information in fleet forecasting 14




Figure 2.5: Aircraft and engines forecast model at Volvo Aero 18 Figure 2.6: Sample aircraft forecast (VAC) 19 Figure 2.7: Iterative scenario construction and evaluation 22 Figure 2.8: Use of business environment scenarios in VIVACE 23 Figure 3.1: The first tier of the initial consensus factors map 26 Figure 3.2: Factors related to passenger traffic 28 Figure 3.3: Factors related to freight traffic 30 Figure 3.4: Factors related to GDP 31 Figure 3.5: Factors related to global trade 32 Figure 3.6: Factors related to business cycle 33 Figure 3.7: Factors related to exchange rate 34 Figure 3.8: Factors related to taxation 34 Figure 3.9: Factors related to politics 35 Figure 3.10: Factors related to subsidy 36 Figure 3.11: Factors related to safety 37 Figure 3.12: Factors related to security 39 Figure 3.13: Factors related to airport capacity 40 Figure 3.14: Factors related to environment 41 Figure 3.15: Factors related to regulation 42 Figure 3.16: Factors related to passenger attitudes 43 Figure 3.18: Factors related to green technology 46 Figure 3.19: Factors related to certification 47 Figure 3.20: Factors related to operating costs 48 Figure 3.21: Factors related to costs of financial services 49 Figure 3.22: Factors related to cost of fuel 50 Figure 3.23: Factors related to ticket price 51 Figure 3.24: Factors related to yield 52 Figure 3.25: Factors related to operator revenue 52 Figure 3.26: Factors related to product and service offering 53 Figure 3.27: Factors related to aircraft fleet 54 Figure 3.28: Factors related to aircraft retirements 55 Figure 3.29: Factors related to demand for new aircraft 56 Figure 3.30: Factors related to demand for maintenance 57 Figure 3.31: Factors related to cost of maintenance 58 Figure 3.32: Factors related to air traffic management 59 Figure 4.1: Sample ‘dimension’ for the description of a future aerospace business

environment 63 Figure 4.2: Initial business environment scenarios 64 Figure 4.3: The VIBES software 87 Figure 4.4: Selection of role, within the VIBES software 88 Figure 4.5: Initial business scenarios available to the user, following their nomination of an

industry role 89 Figure 4.6: Software-based presentation of a pair of business environment scenarios 90 Figure 4.7: Defining the relationship between a pair of scenarios and selected industry metrics, using VIBES’ developer mode. 91 Figure 4.8: Sample screen from the output phase of the VIBES software 92 Figure 5.1: Business environment modelling complements the other descriptive approaches

95 Figure 5.2: Flow of information between the WP2.1.1 activities 96 Figure 5.3: A basic system dynamics model based on Liehr (2001). 99 Figure 5.4: Sub-systems model 110




Figure 6.1: Principal stages of the value chain. 114 Figure 6.2: The basic model of Porter’s Value Chain (source: Porter, 1985). 115 Figure 6.3: Porter’s whole value chain (source: Porter, 1985). 115 Figure 6.4: Detailed model of the value chain 116 Figure 6.5: Operator expenses. 116 Figure 7.1: Perspectives on the value chain 119 Figure 7.2: Research activities 120 Figure 7.3: Summary of contributions to-date and future work 121 List of Tables Table 2.1: Comparison of scenario analysis techniques (based upon Schnaars, in Dyson,

1990) 21 Table 5.1: Summary of the strategies of the two case studies 104 Table 5.2: Delays in the aerospace industry 109 Table 5.3: Definition of variables 109 Table 5.4: Build phases of the model 110




0. EXECUTIVE SUMMARY

The aerospace industry is a major employer and wealth generator. Many nations have made substantial investments to develop and retain world-class aerospace design, manufacturing and assembly capabilities. The industry impacts upon many aspects of society (e.g. travel and the environment) as well as on trade and defence. In order to deploy their resources to best effect, aerospace businesses need a means of understanding, mapping and analysing the future business environment in order to formulate strategies that minimise risks. This document presents a preliminary outline description of approaches to facilitate and support strategic thinking in the sector.

Three key activities are described within this report:

• Understanding and mapping the factors that impact the aerospace business environment.

• Developing a set of initial business scenarios for the sector.

• Exploring possibilities for modelling key business scenarios.

To understand the key drivers and issues influencing the aerospace business environment, a structured analysis was conducted based on academic literature, the trade press, industrial reports, and discussions with industry personnel. The review demonstrated that the industry is facing many challenges particularly in terms of cost-reduction, security, environmental issues and legislation, as well as economic and demographic factors and various industry-specific factors.

The work has identified 31 key factors and the relationships between them. These are illustrated in a Consensus Factors Map - a multi-level, linked map that can be navigated in MS Powerpoint. Initial feedback from the industry indicates that the map provides a comprehensive view of the aerospace business environment. Within the report, the factors are discussed in detail, with the aim of identifying the most important and/or uncertain factors in affecting the future of the industry. A summary review of the ACARE documents has also been produced and included in the appendices.

The factors map has been used to develop a set of 19 initial business scenarios that provide a description of possible future environments for air transport. These have many potentially different impacts on the industries involved in the sector. The scenarios look at the development or key changes in various aspects in the aerospace industry. They describe uncertainties within the sector including demand. Will passengers be offered direct flights or hub connections? Will they fly long haul or short haul? Will there be more freight or passenger traffic? The initial scenarios also envisage changes in the external environment e.g. airport availability, war, fuel availability and the environmental issues. Some of the scenarios explore industry-specific issues such as aircraft age, operator partnerships, power struggles between operator and manufacturer, attitudes to risks, etc.




While these scenarios depict the possibilities of the future aerospace industry, they introduce many variables that may be too complex to handle. A tool for investigating the future scenarios concepts that are most relevant to the key players in the industry is under development. The tool is called VIBES (VIVACE Interactive Business Environment Simulator) and a first draft has been produced. The tool allows information to be gathered on the scenarios that cause the aerospace industry stakeholders the most concern. The output of this tool is a cluster of trends called a ‘theme’. Further development of the VIBES tool and a prototype demonstrator is planned.

The industry currently uses traditional forecasting methods based on trend projection for high level aggregate planning over a 3- 5 year timeframe. The report describes the approaches used by our industrial partners, Rolls-Royce and Volvo Aero Corporation, based on interviews with key personnel. Understanding and analysing future aerospace business environments over longer time horizons can benefit significantly from formal scenario analysis and scenario modelling methods. The report provides an introduction to a range of relevant scenario concepts and techniques.

In order to capture the dynamic behaviour of the market (a key characteristic of the aerospace industry), more detailed simulation modelling is required. A scenario modelling technique called system dynamics is proposed for modelling the dynamic behaviour of the aerospace market. Previous applications of systems dynamics modelling of relevance to the aerospace sector are reviewed. An initial model of the VIVACE business environment sub-systems has been presented for review and approaches for developing more detailed models are described.

Scenario modelling takes a high level perspective on value chain development – a ‘top down’ view. The report also provides an overview of value chain modelling concepts which can provide ‘a bottom up’ approach to developing value chain strategies for the future. These approaches will complement each other in developing innovative and practical value chains for the aerospace industry of the future.

The report outlines the nature of the work and the expected deliverables in the next phase of VIVACE. As well as the development and refinement of VIBES, we aim to extend our systems dynamics modelling work; produce a state-of-the-art review of Value Chain modelling techniques of specific relevance to the aerospace sector; and an updated report on the Future Business Environment that will contain business environment simulation models and a selected approach for value chain mapping. All planned activities require a number of iterations as well as validation from industry partners. We appreciate feedback on any aspects of the business environment, scenario analysis and modelling or value chain work.




1. CHAPTER 1: INTRODUCTION TO THE RESEARCH

1.1. INTRODUCTION This report was prepared for the VIVACE project by the University of Nottingham (UNOTT) with assistance from Volvo Aero Corporation (VAC). It represents the month 11 deliverable D2.1.1_1; ‘Preliminary Description of the Future Aerospace Business Environment.’ This chapter provides an overview of the work being conducted under VIVACE Task 2.1.1; business and value chain modelling. The aims of the work are listed, the approach selected is discussed and the structure of the remainder of the report is described.

1.2. AIMS OF THE RESEARCH VIVACE aims to produce an integrated supply chain that will supply products faster i.e. reduced time to market, more responsive, and cheaper, with benefits coming from reduced cost of development and reduced risk. Task 2.1.1 can contribute towards these goals by allowing the rapid evaluation of the fit between a proposed virtual enterprise and an anticipated future business environment. This could save time, and allow risks to be identified at an early stage. The objectives of the research, as stated in the Document of Work (v1.7) are:

• Define business interfaces and develop models to manage risks and optimise delivery of a new value proposition (balanced with respect to business; cost & lead time and environmental attributes) from a network of partners in a collaborative and distributed working environment.

• Develop simulation models and provide examples to explore how extended enterprises can be formed and act in an aeronautical business environment and to analyse the value chain.

In this phase (D2.1.1_1) it is aimed to present a methodology whereby a wide variety of future business environments can be defined, for the purposes of communication and so that they may be subjected to modelling, simulation and experimentation.

1.3. APPROACH SELECTED The approach to representing the future business environment for aerospace operations, as described in this document, is built upon a detailed understanding of the circumstances prevalent in the group of industries that offer aerospace products and services in the present day. This has been achieved via an extensive literature survey, making use of academic and industry sources, plus questioning of personnel in the aerospace manufacturing




sector. Offerings arising from this side of the work to-date include reviews of some key documents, a map showing the interrelationships between key business drivers, and a software tool meant to allow rough-cut experimentation with theoretical future business environments. The report also identifies state-of-the-art techniques in scenario analysis and system dynamics modelling. This has been identified as highly promising, allowing the business environment themes that are of key importance to the VIVACE project to be identified, and allowing detailed modelling of trends and business performance within a highly competitive market. Some initial models are proposed within this document. Likewise, thought has been given to the scoping of other forthcoming activities within Task 2.1.1; future activities given in the Description of Work document include business interface definition, and value chain modelling. Thus, these are discussed within the report where the findings of the current work bear upon the future direction.

1.4. REPORT STRUCTURE This report is organised into seven chapters; this section provides a brief overview of the content of the remainder of the document. Chapter 2 provides an introduction to business environment modelling; its purpose and the methods that can be employed. Existing approaches to market forecasting at Volvo Aero Corporation and Rolls-Royce are also reviewed. The scope of this activity, with regard to Task 2.5.1, is also discussed. In Chapter 3 the key factors acting upon the aerospace business environment are discussed, including trends that have been identified in the work to-date. Chapter 4 describes the construction of a set of initial business scenarios, allowing the future of air travel to be explored experimentally, while Chapter 5 details forthcoming work to construct computer-based models allowing the risks and benefits inherent in various future scenarios and strategies to be investigated. Chapter 6 discusses the impact of the modelling work upon the value chain, and Chapter 7 provides conclusions upon the work conducted to date.




2. CHAPTER 2: INTRODUCTION TO BUSINESS ENVIRONMENT DEFINITION

2.1. INTRODUCTION This chapter provides an introduction to methods for mapping the future aerospace business environment. While plans in the short term will be centred upon meeting firm customer orders, and in the medium term upon meeting anticipated changes in demand patterns, forecasting methods must change as the timeframe expands. The successful enterprise will be active in business environment modelling at every level. The chapter begins with a brief overview of the forecasting practices employed by two major aerospace manufacturing businesses. For these companies, supplying complex products, assemblies and parts, made using highly-specialised materials and processes, lead times are necessarily long. This has consequences for their road-mapping processes for the future. The 3-5 year timeframe is the subject of market forecasting, while any efforts to anticipate radical shifts in customers’ requirements (and hence sources of risk) must be ever further into the future. Forecasting methods can generally be classified as either quantitative (e.g. causal model and time series methods), or qualitative (scenario writing, Delphi methods, group forecasting, market research etc). The creation of scenarios looks beyond the order book, and forecasts of future orders, offering a response to our inability to know the future. While forecasting methods attempt to predict the future, scenario building develops multiple views of possible future business environments. Plans to exploit and/or contingency plans to survive each anticipated outcome can then be made.

2.2. EXISTING BUSINESS FORECASTING METHODS A key element of the review of business environment analysis techniques was to investigate current practice within the industry. Project partners were approached to discover how they conducted long-term planning, with the aim of identifying current practices, and the future information needs of a collaborative enterprise.

2.2.1. Long-term Forecasting methods employed at Rolls-Royce1 Long-term planning at Rolls-Royce is conducted in a time horizon of from three to five years. This involves regular contact with counterparts in airframe manufacturing including Boeing and Airbus, and, on a more limited level, the smaller aircraft manufacturers. Typically, the forecasts of each organisation are similar at the overall level, although their predictions may

1 A visit to Rolls-Royce took place on August 19th 2004 to discuss our partner organisation’s forecasting needs, and the methods employed. This section represents a summary of the information obtained from Mr Richard Evans, Market Forecasting Manager at Rolls-Royce.




vary when the market is segmented. The more precise process of sales forecasting, conducted in a 2-3 year window, is achieved by other means.

Demand is broken down into segments, each with its own characteristics and trends. There are some 17 different segments, defined by geography (region) or length of flight (inter-region). Examples would be ‘Transatlantic’, or ‘China Domestic’.

To calculate demand it is necessary to take into account aircraft size, measured in passenger seats. Thus, for each segment, a graph can be produced showing the number of aircraft of each size that will be operated within the region. Figure 2.1 shows an example:

Figure 2.1: Sample aircraft capacity forecast

The number of aircraft forecast to be operated in a region is only a partial indicator of demand because there are often empty seats on a flight. To calculate the load factor (productivity), the number of aircraft is divided by Available Seat Kilometres (ASK), to produce a result like that shown in Figure 2.2.

Figure 2.2: Available Seat Kilometres by aircraft size

With productivity known, the total level of activity can be estimated, giving indications of the requirement for aircraft capacity, and hence engines. It is also possible to investigate the mix of flights, in terms of those flying between primary airports, and secondary ones. Demand




can be broken down into a matrix showing flights between major city pairs, minor airports, or a mixture of the two (Figure 2.3). Subscriptions to sources such as ‘Airline Intelligence’ provide schedules that will yield this information.

Figure 2.3: Primary and secondary node breakdown Similar calculations are also performed for freight, where the unit of measure is tonnage (and available freight tonne kilometres). In each case, minor operators are not examined in detail. The top 100 fleets give an adequate indication of the trends within the market (though this might not be adequate for the business jet market.) Figure 2.4 shows sources of information used to build such a plan:

Figure 2.4: Sources of Information in fleet forecasting Thus, forecasts are based upon the analysis and projection of trends, not from macroeconomic models. Furthermore, since yield varies tremendously, little work is done on airline revenue forecasting.




2.2.2 Forecasting methods employed at Volvo Aero Corporation2 Here we go through the way that Volvo Aero predicts the nature of the market for engines, spares and services. The focus of this study is long-term planning, which is to say 20 years. Forecasting of this kind involves regular contact with different players within the aviation industry, such as airframe manufacturers, aero engines manufactures and a lot of different independent specialists and forecast providers. Volvo Aero also uses different AB Volvo internal departments that have specific economical knowledge. The forecast that is done at Volvo Aero is top down demand forecast. We will come back to this later. This is not exactly the same as sales forecasting, which is more a precise process detailing engine build volumes in a 0-3 year window. The sales forecast is based on this forecast, but also on more specific information from the costumer. Typical parameters that will be observed in the forecast process are:

• GDP ● Orders and deliveries • Oil price / Jet fuel price of aircraft • Yield ● Backlog • RPM • Cargo traffic • Capacity and load factor ● Parked aircraft • Airlines share of GDP ● Aircraft flight hours • Airlines net result ● Engine flight hours

The parameters on the left side are general parameters that will be used in both details and overall analyses on different markets. On the top right side there are parameters that are specifically related to new engine markets. On the lower right side there are parameters that are specifically related to overhaul markets. We will come back to the difference. There are different types of forecast methods that are used to predict the future. In general we can say that trend analysis of a qualitative or quantitative type is used. The central focus is to describe the air traffic and cargo traffic growth. That means that all the other predictions are only made to develop the general knowledge about the market, so that you can support this prediction. When Volvo Aero does its forecast they make a clear different between new engines market and overhaul market. If we look at new engine market first, they use the following process.

2 This section represents a summary of different interviews at Business Development and Strategies at Volvo Aero.




GDP Change Yield Change

Traffic Growth (RPM)

Load Factor (%)

Required capacity (ASM)

Aircraft SizeAircraft productivity

Growth (# Aircraft)

Required fleet

Replacement (# Aircraft)

Airline policy

Aircraft age

EnvironmentalLegislation

Figure 2.5: Aircraft and engines forecast model at Volvo Aero The fundamental in Volvo Aero’s top down demand forecast method is to describe the traffic growth based on GDP and Yield changes. Then they look at load factor (percent of occupied seats), because there are often empty seats on a flight, and if you want to calculate the required capacity (ASM) you need to take load factor into account. Load factor is also an expression for productivity. Now you have the demand for aircraft, but to be able to predict the required fleet, you need to look at the numbers of replaced aircraft. And to predict that you need to look at airline policy, airline net result, environmental legislations and aircraft age. Based on all this information it is possible to describe the demand for aircraft and engines. For the first period of the prediction (sort term) Volvo Aero also take orders and deliveries of aircraft and backlog into account. On the other hand we have overhaul market forecast. Here Volvo Aero follows the same process but they are not only interested in the required fleet on the market, but also how many hours the different aircraft are flying. So to complete the forecast for overhaul market is necessary to take into account utilisation per day of the different aircraft. The result of this will be number of flying hours per aircraft and engine as shown in figure 2.6.




Figure 2.6: Sample flight hour forecast Volvo Aero

When you know have many hours the different engine will fly, you need to know the shop visit rate. The shop visit rates describe who many hours an engine can fly before it needs an overhaul. Based on this you have the expected numbers of shop visits. But in overhaul market forecast Volvo Aero want to know the value of the shop visits, not only the numbers. To find the value you first of all need to know the market price for an overhaul on the specific engine. This market value can fluctuate over time based on the demand and supply, so you also need to forecast that. And to finish your forecast you need to know the split between material and labour, so you can find your added value and then the value for the company. This forecast will be the basis for many decisions. For that reason it is important to understand the meaning of the prediction; in general this involves the difference between information and intelligence. Information is factual. It concerns numbers, statistics, scattered pieces of data about parameters, and companies and their activities. Information often appears to be telling something but in reality it’s not. You can’t make good decisions based on information no matter how accurate or comprehensive the information is. Intelligence, on the other hand, is a collection of information pieces that have been filtered, distilled and analysed. It has been turned into something that can be acted upon. Intelligence, not information, is what managers need to make decisions. Another term for intelligence is knowledge. People usually have too much information and too little forecasting intelligence, and it is hard to make the right decisions. For that reason much forecasting work together with scenario planning is done to analyse the predictions and develop knowledge.

2.3. INTRODUCTION TO SCENARIO ANALYSIS Business environment mapping through the use of scenarios is an important part of business strategy formulation. The approach promotes consideration of viable responses, when faced with shifts in the business environment, such as an undesired trend that would lead to a loss of revenue or market share.




The approach can also be used to test the assumptions inherent in a company’s forecasting process, investigating the confluence of forces that characterise the anticipated future. Scenario modelling may also be instigated after a problem is encountered, providing a structure for rethinking the company’s views on the future, e.g. after an oil crisis, or any discontinuous change. Where quantitative forecasting methods may fail because there are no clear trends, scenario techniques are potentially most valuable. In one of the key sources on scenario planning, Ringland (2002) defines scenarios thus:

”Scenarios are possible views of the world, providing a context in which managers can make decisions. By seeing a range of possible worlds, decision makers will be better informed, and a strategy based on this knowledge and insight will be more likely to succeed. Scenarios may not predict the future, but they do illuminate the drivers of change: understanding them can only help managers to take greater control of their situation.”

(Ringland, 2002, p.2) Scenario analysis methods differ from conventional prediction techniques such as forecasting because they examine the behaviour of future environment as well as demand, and they can take multiple perspectives of the future. Future scenario development is based on taking multiple views of alternative future business environments. Therefore a number of future scenarios are developed in parallel to provide learning about the responses that a business might enact. Because we are not primarily attempting to predict which outcome is the most likely, it is possible to hold in mind a diverse set of possibilities, while simultaneously looking for responses that offer results as close to ‘win/win’ in the future as possible. A scenario centred upon maintenance activities might postulate an increase in the demand for maintenance (perhaps brought about by increasingly stringent legislation), a continuation of the present-day level of business, or a decrease (perhaps due to aircraft being scrapped at an earlier age, or during a period of reduced demand for air travel). In each case, the set of scenarios may then be explored to discover what it means for the industry stakeholders; manufacturers, operators and others.

2.3.1. Initial Scenario Formulation A number of methods have been used by strategists to approach the problem of future scenario development and analysis. Some approaches are strongly qualitative and are based on discussion of the key issues; others are combined with forecasting and probability assessment techniques. Godet (2001) describes a highly quantitative approach to the construction of scenarios; however, as Section 2.2 has shown, the aerospace industry already has well-developed methods of quantitative forecasting. The qualitative alternative allows a holistic approach that more readily addresses complex business environments including the virtual enterprise. A wide variety of techniques may be employed to generate business environment scenarios, including the following:




• Forums for identifying key issues (business environment characteristics and responses)

• Mental models

• Narrative techniques providing a description of possible, distinct futures

• Cross-impact analysis

• Identification of present-day environmental factors

• Identification of ‘surprise factors’ Some of these techniques require little more than workshop-type discussions between experts, while others are more structured. Cross-impact analysis, for example, is based on the principle that every issue is interconnected. It calls upon the judgment of industry experts to identify the cross-impacts that can be expected, and estimate their magnitude. Heijden (1996) considers it particularly important to involve subject experts in “strategic conversations”. Alternatively, some quantitative tools have been proposed, although not widely adopted by practitioners e.g. probabilities and odds ratio techniques. Some practitioners argue that mathematical calculations are inappropriate in this field, since they limit thinking to a narrow set of variables.

2.3.2. Scenario Construction Methodology There are essentially two schools of thought in the construction of future business environment scenarios. Kahn (1968) advocated intuitive methods; “Simply thinking about the problem, whilst Helmer (1991) focuses upon methodologies to structure the problem. Regardless of the exact method adopted, the time horizon that should be used in scenario analysis should represent the commitment of resources of the business. Existing scenario analysis projects have typically used timeframes of between 5 and 15 years – entirely compatible with the VIVACE work that considers the state of air transport up to 2020. It should be remembered that the purpose of scenario construction is not to generate a prediction of what is felt to be most likely. Thus, most scenario approaches use three scenarios, exploring a low, middle and high outcome for the variable under study – an optimistic and a pessimistic scenario, and then a base-line scenario. This should represent a ‘surprise-free’ scenario with no changes. However, the latter may not be the most likely. Table 2.1 shows the key characteristics of some of the principal scenario formulation techniques. Each of the scenarios in the set should be plausible – it is a mistake to focus on the middle, ‘status quo’ scenario. When determining the extent of variability to be explored, some practitioners employ a ‘best possible’ and ‘deadliest enemy’ approach. Having now identified the issues/factors that are of interest, and constructed a spread of scenarios that allow variation in each factor to be explored, the net change of a group of scenarios can be investigated. This group of scenarios is called a theme. As Figure 2.7 shows, factors go to make up scenarios, scenarios may be grouped into themes, and a




theme may then form the basis of a modelling exercise. Aerospace industry factors, scenarios and themes, and modelling are discussed in Chapters 3, 4 and 5 respectively.




Table 2.1: Comparison of scenario analysis techniques (adapted from Schnaars, in Dyson, 1990; see also other studies in Chapter 5)

Application

British Airways

Paris Airport

Authority

Xerox Corp.

General Electric

Royal Dutch / Shell

General

application

General

application

Low cost

Flight operators

Scenario analysts

Moyer (1996)

Godet (2001)

Linneman & Klein (1983)

Wilson (1978)

Schoemaker & van der Heijden (1992)

Becker (1983)

De Kluyer (1980)

Salge & Milling (2004)

Number of

scenarios used

2

6

3 or 4

3 or 4

None given

3

3

4

Length of scenario

descriptions

None given

None given

1 or 2

paragraphs

None given

None given

None given

None given

1 or 2 paragraphs

Use of base

scenario

None

Most likely

None

Surprise free

None

Most likely

Most likely

No

Multiple scenarios

Themed

Themed

Themed

Optimistic / pessimistic

Themed antithetical



Themed

Reduction of factors

Expert opinion

Surveyed of

expert opinion

Considered only

key factors

Scoring by

probability and importance

Selected by

management team

Considered only

key factors

Considered only

key factors

Selected by modellers

Selection of scenarios

Conformed to themes – wild gardens and

planned structures

Constructed from matrix

analysis

Selected from

plausible combinations of

key factors

Scenario writing

& impact analysis

Defined boundaries

of scenarios

Selected plausible

combinations of key factors

Judgmental

translation into optimistic /

pessimistic and most likely

Based on themes

Use of probabilities and cross-impact

analysis

No probabilities or cross-impact

analysis

Probabilities

used

No probabilities or cross-impact

used

No probabilities used but cross-impact analysis

is uses

None given

No or cross-impact used probabilities

used

Probabilities used but no cross impact

No probabilities or cross-impact used




Figure 2.7: Iterative scenario construction and evaluation

2.4. USE OF SCENARIO ANALYSIS WITHIN VIVACE Scenario analysis and scenario modelling have great potential to map the future aerospace business environment. The approach allows a systematic consideration of issues such as changes in sources of supply, the entrance of new competitors, the impact of legislation, etc., all of which present opportunities or threats, and require a planned response. Ultimately, scenario analysis might be used to investigate the core competences and infrastructure required by the European aerospace industry of 2020. Given a set of future circumstances, the supply chain will need to respond to the challenges of a new business environment. These responses may well alter their product and service offerings, enter into risk and revenue sharing partnerships, and other strategic decisions that will be made in order to survive and thrive in the future. The scenario analysis approach employed for the VIVACE work differs from that commonly used because it is necessary to model the business environment – and assess the responses – of the entire value chain rather than the circumstances of a single organisation. Furthermore, it complements rather than supplants the forecasting techniques currently employed within aerospace manufacturing industries (See Section 2.2) because it allows forward planning to be extended over a longer timescale, which is appropriate given the complexity (and consequently long product lead time and lifecycle) of aerospace systems.

2.5. CONCLUSIONS This chapter has described two approaches to the representation of the future business environment. A brief overview of the forecasting techniques employed at partner organisations was presented, plus an introduction to the scenario analysis techniques that can be employed where environmental characteristics are particularly complex. Faced with discontinuous changes, dynamic behaviour and the increasing degree of uncertainty that develops as the focus is moved further into the future, scenario analysis can be extremely useful in decomposing complex interactions (without oversimplification) so that they can be understood and acted upon.




The scenario modelling approach proposed supports an extensive range of possibilities in the future business environment, and is likely to be beneficial to project partners in their own work package; Figure 2.8 illustrates commonality with other work packages. In Chapter 3, the business factors and drivers acting within the aerospace business environment are discussed. Those that are of concern to industry stakeholders will form the basis of the themes that are selected for closer investigation, including modelling using system dynamics. The formulation of themes from a set of initial business scenarios is discussed in Chapter 4, and possible approaches to modelling work are discussed in Chapter 5.

Figure 2.8: Use of business environment scenarios in VIVACE




3. CHAPTER 3: BUSINESS DRIVERS AND FACTORS

3.1. INTRODUCTION In defining the aerospace business environment, the first step is to consider the environmental influences that have been particularly important in the past, and the extent to which future changes might introduce new influences, or make existing influences more or less significant in the future. This chapter describes the process by which a map of key factors for the future aerospace business environment was generated. It presents a holistic view of the industry, taking into account diverse viewpoints, particularly those of operators and manufacturers. Each of the factors is then discussed in detail.

3.2. THE LITERATURE SURVEY CONDUCTED The aerospace industry is highly complex, influenced by various forces in the environment from economics, society, politics and development in technology. In order to understand the factors and drivers at work in the wider environment, an extensive review of sources were conducted. The key sources reviewed were:

• Publications from the Advisory Council for Aeronautics Research in Europe (ACARE)

• Industrial reports: Rolls Royce, Volvo Aero Corporations and Airbus

• Trade associations e.g. European Metalworker’s Federation (EMF), International Air Transport Association (IATA) and Air Transport Association (ATA)

• Trade press e.g. Aviation Week and Space Technology (AWST), Interavia and Flight international.

• Consultancy report e.g. McKinsey Quarterly

• Market analysis reports: Market Intelligent (Mintel)

• Academic journals e.g. Journal of Air Transport Management and Aircraft Engineering and Aerospace Technology

Review and structured analysis of the literature enable us to identify the issues that are of particular importance to the aerospace industry. In general, several key issues widely discussed in the current literature are cost-reduction, security, environment and regulations. Most of the literature reviewed highlights that in order to ensure long-term growth of the aerospace industry costs need to be reduced. The question is how it can be achieved. The airline industry is certainly the most pressured to cut their costs. However, recent publications from the airline industry association argue that in order to reduce the costs in the total value chain, some of the airline’s service providers such as airport owners and air traffic controllers need to have clearer action plan to cut their costs. Security of air travel is another issue widely addressed in the literature. While all players in the industry agree that any possible measures should be undertaken to ensure a much more secure air travel, there is an ongoing debate on who should pay for the costs associated with




designing and implementing the new security measures. Airline industry strongly argues that the government should pay for the security measures. Another main issue relates to the impact of air travel on the environment. Legislators and environmentalists have made it clear that the aerospace industry must continue their effort to minimise the environmental impact of air travel. This view is shared by key players in the industry. However, there are different views on how the goals could be achieved. Governments in several countries are thinking of introducing so called ‘environmental charges’ or fuel taxes. As published in trade press and newsletter, the airline industry strongly opposes such charges and proposes the use of quieter aircraft as a win-win solution. Many aspects of the regulation are expected to influence the future of aerospace industry. These include regulation on air traffic management, alliances between operators, safety and environment. In addition to these issues, many other factors identified from the literature are also expected to influence the future of the aerospace industry. In total, thirty-one factors were identified as particularly relevant, influencing the future of the aerospace industry. Having identified these factors, it was also found that these factors potentially relate to one another in a systemic way. Therefore, a method to not only lists the factors but also show relationships between them is necessary. Initially, several methods are tried to describe the factors in the aerospace business environment. Finally, a simple graphical method describing these factors and relationship between them are chosen. The method is referred to as factors mapping, which will be described in more details in the following section.

3.3. FACTORS MAPPING OF THE FUTURE BUSINESS ENVIRONMENT Factors influencing the aerospace industry are depicted in an initial consensus factors map. The factors map aims not merely to provide a list of the factors influencing the aerospace industry, but to show the relationships between them. The factors map is presented in a two-tier format. The first tier provides a top-level overview of the factors and inter-connections between factors. More detailed descriptions of the related issues influencing each factor are described in the second tier. Figure 3.1 shows the first tier initial consensus factors map.




Figure 3.1: The first tier of the initial consensus factors map

AircraftfleetAircraft

fleet

Demand fornew aircraftDemand for

new aircraft

Global trade

Business cyclePassenger

attitude

Security

GDP

Taxation

Subsidy

OperatorRevenueOperator

RevenueYield(Price x RPK)Yield

(Price x RPK)

Product andServiceoffering


EnvironmentGreen

technology

OperatingCostsOperating

Costs

Airportcapacity

RegulationSafety

Exchange rateCost of

financialservices

Cost offuel

Demographics

Certification

AircraftretirementAircraft

retirement

Demand formaintenanceDemand for

maintenanceAir traffic

management

Price ofticketPrice of

ticket

No ofPassengersNo of

Passengers DistanceDistance

Passenger Traffic

No.ofFreight (ton)No.of

Freight (ton)

Freight Traffic

Politics

Politicalfactors

Economicfactors

Technologyfactors

Socialfactors

Influence

Macro-environment factors

IndustryfactorsIndustry

factors

Cost ofmaintenanceCost of

maintenance




As shown in figure 3.1, factors are presented as nodes. Factors in the wider or macro environment are grouped into political, economic, social and technological factors. Factors that are more specific to the aerospace industry such as passenger and freight traffic, operating costs, demand for new aircraft, etc., are also identified. Relationships are presented by placing arrows between the factors. For example, passenger traffic is influenced by Gross Domestic Products (GDP), demographics, airport capacity, security, politics and many other factors. Passenger traffic, in turn, influences many other factors such as yield, aircraft retirement, demand for maintenance, etc. For each factor presented in the first tier, a more detailed map exists. The section that follows describes each of those maps in detail.

3.4. DETAILED DESCRIPTION OF FACTORS The influences that contribute to each of the factors appearing in the first-tier factors map are discussed in this section. When the data is publicly available, trends relating to a factor that can be presented in the form of quantitative numerical estimates e.g. passenger or cargo traffic growth, demand for new aircraft, obtained during the literature review process, are noted.

3.4.1. Passenger Traffic Passenger traffic, typically measured by the number of passengers multiplied by the number of kilometres they fly, is one of the key factors in the aviation industry. It is usually represented as Revenue-Passenger-Kilometre (RPK). Passenger traffic is influenced by a number of different factors (figure 3.2).




Figure 3.2: Factors related to passenger traffic

Demographic factors such as population growth, breakdown of political boundaries, increased wealth, and migration (Rolls Royce, 2004) as well as economic growth (Boeing, 2004a) and the continuing trend of global trade are some of the main driving forces for growth in air passenger traffic. Costa et al. (2002) relate the ups and down in passenger traffic with business cycle. The relationships between passenger traffic and the business cycle are described in more detail in section 5. Security, safety, air traffic management and airport capacity are factors that may constrain growth in air traffic demand. The Aerospace Innovation and Growth Team (2003) quoted predictions made by the International Air Transport Association which stated that Europe’s air transport system will not be able to meet demand by 2011 without changes. A number of political issues such as war and bilateral agreements between countries also influence passenger traffic. The Iraq war in early 2003 is one of the factors contributing to decreasing passenger traffic in that year (Donne, 2004). Passenger attitude with respect to comfort and convenience is expected to influence passenger traffic. Increased convenience may motivate more people to fly. At the same time, the products and services offered by the aerospace industry may influence the number of air passengers. Passenger traffic, in turn, influences the price of tickets, aircraft retirements, demand for new aircraft and demand for maintenance. Different sources of information present different views on the trend in passenger traffic. Two of the key players in the aviation industry, Boeing (2004a) and Airbus (2003) gave optimistic views of the growth in passenger traffic. They predict that passenger traffic will grow approximately 5% per annum over the next 20 years. The ACARE scenario assumed that by 2020+, air transport growth will be tripled despite cyclical variations in annual growth

Safety Global trade

Security

Airport capacity

GDP

Politics

PassengerTraffic Business

Cycle

Price of ticket

Product & service offering

Aircraft fleet

Demand for air travel

Passenger attitude Demographics

Demand for new aircraft

Demand for maintenance

Aircraft retirements




(ACARE, 2002). Costa et al. (2002) describe the trend in passenger traffic with more caution. They warns that whilst air travel has long enjoyed growth rates well above GDP, these high growth rates have eroded over time and the gap between traffic growth and GDP growth has been shrinking. Passenger traffic growth is expected to vary across different air travel markets. Passenger traffic is expected to grow strongly on routes serving the Asia-Pacific region while the European and North America markets have matured with lower growth rates (Boeing, 2004a; Airbus 2003; Rolls Royce, 2004).

3.4.2. Cargo (freight) traffic In addition to passenger traffic, cargo or freight traffic is another important driving force in the aviation industry. Cargo traffic is usually measured in Freight-Tonne-Kilometres (FTK). The primary driver for growth in air cargo traffic is economic activity, as measured by world Gross Domestic Product (Boeing, 2004b). The continuing trend in global trade means that cargo traffic is seen as a potential growth market (Rolls Royce, 2004) and a source of revenue for operators. As shown in figure 3.3 freight traffic is also influenced by many factors including airport capacity. A study on air passenger and cargo flows conducted by Matsumoto (2004) provides an example of how airport capacity constrains cargo traffic. He argues that the decline in Tokyo’s role as a hub for cargo traffic over the period of his study is due to the limited capacity of its international airport. As freight traffic contributes to aircraft utilisation, it is expected to affect demand for aircraft maintenance. Freight traffic also influences the aircraft fleet. ACARE (2002) proposes several assumptions with respect to freight and aircraft fleet. ACARE predicts that during the next 20 years freight transport will develop significantly and the world aircraft fleet will be composed of a larger fleet for freight transportation. Both Boeing and Airbus predict that cargo traffic will continue to grow more rapidly than the passenger market. Boeing and Rolls Royce predict that cargo traffic will grow by over 6% per annum while Airbus predicts 5.7% per annum growth. High growth in air cargo market and the inability of belly-hold capacity to keep pace means that the need for fleets of large dedicated cargo aircraft will increase (Airbus, 2003; Rolls Royce, 2004). ACARE (2002) also predicts that passenger and freight transport will be more separate to optimise their respective operational costs.




Figure 3.3: Factors related to freight traffic

3.4.3. Gross domestic product Gross Domestic Product (GDP) is seen as principal measure of material well being and economic productivity (De Long, 2002). GDP is influenced by many factors such as the level of technology, capital investment, labour efficiency, population growth and savings rate (figure 3.4). GDP appears to be the main macroeconomic indicator used by key players in the aviation industry to predict the growth in passenger traffic. Boeing (2004a) states that GDP growth explains most of air travel growth. Airbus (2003), on the other hand, argues that in recent years the dependence of passenger traffic on GDP has become weaker as other demand drivers become more important. They argued that travel decisions are increasingly influenced by the affordability of tickets. Several academic papers also use GDP in predicting air traffic, albeit with varying results. Guzhva & Pagiavlas’ (2004) study on decomposing the effect of the September 11th from macroeconomic influences found that there is a strong dependency between airline performance in terms of passenger traffic and general economic conditions measured by real GDP. Matsumoto’s (2004) work, on the other hand, found GDP to be of lessening importance in explaining air traffic flows.

Operatorrevenue

FreightTraffic

Globaltrade

Aircraftfleet

Demand formaintenance

Cost ofalternativetransport

Airport capacity




Figure 3.4: Factors related to GDP

Industrial forecasts (Boeing, 2004a; Rolls Royce, 2004) predict that in the next 20 years, annual world economic will grow by around 3%. Rolls Royce (2004) uses economic growth in different regions to identify emerging markets. Although GDP per capita in many Asian countries are quite low and the vast majority of the population is below the air travel threshold, Rolls Royce (2004) sees these markets as having huge growth potential. The economies of most Eastern European countries and in the former Soviet Union continue to grow, representing fast growing markets for air travel, particularly in the new EU entrant states.

3.4.4. Global trade In the past three decades we have witnessed continuing trends of global trade. Many of the goods offered in the market today are made, grown, designed or managed in different regions of the world (External Advisory Group for Aeronautics, 2000). As shown in figure 3.5, global trade is driven by various factors including free trade agreements, the emergence of large ‘domestic market’ such as NAFTA and EU, the emergence of new markets such as China and India, and significant cost differences between regions in the world.

Gross domesticproduct

Global trade

Population growth

Economic cycle

Passengertraffic

Technology

Labour efficiency

Depreciation rate

Savings rateExchange rate

Taxes

Inflation

Government incitement




Figure 3.5: Factors related to global trade The globalisation of business depends on the existence of flexible, inexpensive air transport to connect the dispersed operations (External Advisory Group for Aeronautics, 2000). The continuing trend of global trade means that:

• Increasing numbers of people travel cross-national borders for business purposes.

• Accelerating movement of goods across the globe. Thus, global trade is certainly one of the major driving forces for air passenger and cargo traffic (Rolls Royce, 2004). The International Air Transport Association (2004) in their annual report highlights that the emergence of Chinese economic strength is and will continue to drive freight traffic and long-haul premium travel to and from the region.

3.4.5. The business cycle Business cycle refers to well-established longer term fluctuations in production and employment that affect major economies. Some factors related to business cycle are shown in figure 3.6. Business cycle relates closely to production and employment. Periods in which production grows and unemployment falls are labelled as macroeconomic expansions or boom. On the other hand, periods in which production falls and unemployment rises are called recessions or depressions (De Long, 2002).

Global trade

Passengertraffic

Gross domesticproduct

New markets

Free tradeagreements

Freighttraffic

Cost differences between regions

Information & communication

Technology




Figure 3.6: Factors related to business cycle The nature of the aviation industry is argued by many sources to be highly cyclical (European Metalworkers’ Federation, 2003; Donne, 2004). Costa et al (2002) describes how the economic cycle affects the business of the airline industry and the aerospace manufacturer. The airline industry has in the past experienced growing passenger traffic, strong yields and revenues in boom periods. In contrast, weakening GDP in depression periods lowers demand.

3.4.6. Exchange rates A textbook definition of exchange rate is the relative price of foreign-made goods in terms of home-produced goods (De Long, 2002). As shown in figure 3.7, the exchange rate is related to other economic issues including foreign reserves, government policy, speculation, balance of trade, and inflation or deflation. The exchange rate, particularly the Euro and sterling against U.S. Dollar, affects the cost and the revenue of the European aerospace industry. As reported by Sparaco (2004), the European civil transport manufacturer’s revenue is cashed in U.S. dollars, while roughly 50% of its costs are in Euro. Airbus’s supply chain, for example, is working in U.S. dollars not in Euro. Thus, the weakening of the dollar against the Euro starts to alarm the European aerospace industry. However, Sparaco (2004) also quotes the argument from Antoine Gelain, head of HighStrategy, an aerospace/defence consultancy, who suggests that fluctuation in exchange rates is a recurring issue that European companies should expect and integrate in their long-term strategic planning.

Production

Businesscycle

GDP

Passenger traffic Policy

Employment

Interest rate Inflation/deflation




Figure 3.7: Factors related to exchange rate

3.4.7. Taxation Different form of taxation influence many players in the aerospace industry. Figure 3.8 shows some issues related to taxation, which influence the aerospace industry.

Figure 3.8: Factors related to taxation

Departure tax is a cost that passengers have to pay in addition to ticket price. In recent years, passengers flying low cost airlines often have to pay more for departure tax than the ticket price. Corporation tax certainly influences companies’ revenue. But, more pressing

Departure tax

Corporation taxTaxation

Airline revenueFuel tax

Depreciation

Foreignreserves

SpeculationOperating costs

Balance oftrade

Exchange rate

Inflation /deflation

Airline revenue

Governmentpolicy




issues facing the aerospace manufacturer are fuel tax and governments plan to impose so called ‘environmental taxes’. Aviation fuel is not currently subject to tax. However, Learmount (2004, p. 13) reports the UK Department of Transport statement that ICAO policy on the tax exemption of aviation fuel has been questioned in some states. He reports further that in the recent assembly of ICAO there was an implicit acceptance of the fact that some form of pollution charging is possible beyond 2007. The IATA strongly opposes the imposition of fuel taxes and emission charges (IATA, 2004). They argue that such environmental taxes may compromise airlines financial health without bringing any measurable environmental benefit. While such tax is arguably meant to encourage air transport to become ‘greener’ or more ‘environmentally friendly’, the air transport industry do not want such funds to be used by governments for non-aviation related activities (Donne, 2004).

3.4.8. Politics As shown in figure 3.9, the world political situation influences the commercial aerospace industry in many ways.

Figure 3.9: Factors related to politics

Political situation relates to security and affects passenger traffic. War in a certain region strongly affects passenger traffic and eventually the performance of the airline industry. Following the first Gulf war, air traffic plummeted, resulting in an airline industry loss over $13 billion (Air Transport Association, 2003b). Air Transport Association (2003a) reported that in the month following the second Iraq War in 2003, passenger traffic was down 17.4 % compared with the same period the previous year. Most recently, with an increasing threat of terrorism, many governments have issued warnings against unnecessary travel into troubled countries or regions. This most certainly affects the passenger traffic.

PoliticsSecurity

Economiccycle

Regulations

Passengertraffic

Cost of fuel

Air traffic management




Issues in regulations are also highly political. Air traffic management is currently regulated through bilateral agreement between countries. Due to political and national consideration, there is also regulation on airline national ownership that restricts cross-country mergers. The political situation represented in government policies may influence the market behaviour and economic cycle. Finally, government policy with respect to fuel taxation may influence costs of fuel.

3.4.9. Government subsidy Government subsidy is a highly political and important issue as it may affect revenue of the key players in the aerospace industry (figure 3.10).

Figure 3.10: Factors related to subsidy

The aerospace industry is characterised by high development costs. It also requires big capital investment to ensure its long-term competitiveness and sustainable growth. There is an ongoing debate with respect to sources of funding for development projects (European Metalworkers’ Federation, 2003), especially for new ‘green technology’. One of the long-term risks raised by Aerospace Innovation and Growth Team (2003) is regarding the large imbalance between the support provided by other governments to their civil aerospace industry, particularly the USA, and that in the UK and Europe. Despite the existence of subsidy regulation such as the 1992 US-EU agreement on Trade in Large Civil Aircraft and the 1994 WTO Agreement on Subsidies and Countervailing Measures, the Airbus vs. Boeing subsidy debate has been raging for more than three decades (Macrae, 2004). The most recent case highlighted in the trade press is the 7E7 funding. According to Macrae (2004), the proposed structure of launch funding for the Boeing 7E7 clearly violates global and plurilateral subsidy regulations. Macrae (2004) quoted a study by Prichard & MacPherson (2004) who calculated that a substantial proportion (46%) of the estimated $13.4 billion in launch funding proposals consists of actionable or prohibited subsidies under both the 1994 WTO-SCM Agreements and 1992 US-EU Agreement in Large Civil Aircraft. If Airbus responds to the 7E7 subsidy package with subsidies for Airbus products then this could lead to a “subsidy war”.

PoliticsSubsidy

Revenue

Green technology




Furthermore, the USA budget for military or defence aerospace sector is greater than all the European military budget put together (European Metalworkers’ Federation, 2002). As some of the innovation and technology developed in the defence sector may be used in the civil sector, it could be argued that the European aerospace industry is faced with significant disadvantages.

3.4.10. Safety Safety is a major issue in the aerospace industry. It relates to other factors as shown in figure 3.11.

Figure 3.11: Factors related to safety

Generally, air travel is considered as a safe mode of transportation (ACARE, 2002). A great deal of effort has gone into the creation of more reliable airframes, engines and software, and this has definitely brought dividends. Motevalli and Stough (2004) note that due to the high concentration of fatalities, airline accidents (although very rare) often attract great publicity, which may influence passenger attitude to flying. Thus, they argue that safety standards for aviation must surpass those that would be supported from a statistical and a risk/benefit point of view in comparison with other modes of transport. Safety issues featured prominently in the ACARE (2002) study. In the ACARE report, safety is described as depending on three aspects:

• The technology, system design and operations

• Regulation including certification and qualification

• The human performance to operate the whole chain of air transport activities To ensure that new aircraft satisfy the safety requirements, strict certification standard has to be followed. Maintenance is an important aspect to ensure that the aircraft maintain its performance particularly in terms of safety. Strict safety regulations also force airlines to continue to modernise their aircraft fleet.

Regulations

Training

Safety

Passenger attitude

Certification

Aircraft fleet

Air traffic control

Maintenance

Security




ACARE (2002) aims to maintain confidence that air travel will not only remain safe, despite greatly increased traffic, but also will reduce the incidence of accidents. Incidents take a wide variety of forms. The principal airline accident causes are pilot error (Controlled Flight Into Terrain or CFIT) and mechanical failure. To reduce accidents due to pilot or human error, training of pilots and cabin crew is crucial. Other major causes of disasters include mid-air collisions and accidents while taxiing. The goals set by ACARE in terms of safety are to reduce accident rate by 80% and reduce human error and it consequences. More detailed descriptions on main research routes to reach these goals can be found in ACARE (2002). A goal of zero accidents is unrealistic, but the target continues to be approached. Technologies that will further enhance safety include better airborne radar and other instruments, plus better radio systems, allowing controllers to communicate more reliably with air crews. Many of the innovations that have improved safety originated in the military, prominent examples include radar and fire suppression technologies. A related factor is security, since some problems such as terrorism impinge upon passenger safety.

3.4.11. Security Following the 11th September terrorist attack, increasing the level of security of air transport has become a major concern for society (ACARE, 2002). Security has a significant impact on passenger traffic (Figure 3.12). After 11th September, the Air Transport Association (ATA) press releases report that passenger traffic on the scheduled services of ATA member airlines declined 34.2% in September, 23% in October, 19.8% in November and 14.2% in December 2001, compared with corresponding months of 2000 (Air Transport Association, 2001a – 2001d). In addition to terrorism, smuggling is also an issue of security. ACARE (2002) separate security from safety issues, as they considered security as essentially a political issue. Political guidance and leadership will be required to work out the measures needed. ACARE (2002) identifies challenges in three areas of security:

• The security of navigation and ATM infrastructure

• Airport security

• Airborne security The goals are to establish zero hazards: 1) from failure of the Navigation and ATM system through hostile action, 2) from an aircraft being hijacked on the ground and 3) from hostile action whilst in flight. More detailed explanations on the research routes to reach these goals can be found in ACARE (2002). Further information with respect to measures developed to increase airport security can be found in Mintel Report (2001a). Increasing security measures come with enormous costs. There is an ongoing debate regarding who has to carry these costs. The airline industry argues that the government should be responsible for the costs of security (IATA, 2004).




Figure 3.12: Factors related to security

3.4.12. Airport capacity In overcrowded countries the number of passenger journeys may be constrained by airports and the ways that they are operated. In such a climate, the right to operate a flight from a particular airport – a slot – is valuable in itself and may became more so. As reported by Moxon (2004), the European airlines are preparing for a battle with the European Commission as they propose to introduce a market-based approach to replace the current system for slot allocation. Other factors related to airport capacity are depicted in figure 3.13. When operators are unable to increase the number of flights, they can raise prices until demand matches supply. Some changes may remove the constraint. For example:

• Allowing a new airport to be built.

• Allowing an additional runway at an existing airport. Many major international airports are heavily congested while some have limited scope for physical expansion. Due to high costs, increasingly fierce environmental objections, and governmental prevarication and delays, few, if any, totally new ‘greenfield’ inland airports are likely in most affected countries. This implies that all major new developments probably will be concentrated on upgrading existing airports, mostly with new and/or expanded terminals, and only a limited number of new runways (Mintel Reports, 2001b). Similarly, the ACARE (2002) scenario stated that airports will remain a scarce capacity.

Smuggling

Security

Terrorism

Policing

Passenger Traffic




Figure 3.13: Factors related to airport capacity

Other alternatives to tackle the airport capacity constraint are: • Allowing night flights, or a greater number of flights per day (the constraint may be

based upon aircraft noise, and newer engine designs tend to be significantly quieter)

• Operating larger aircraft (this may well require a runway extension – itself a contentious issue, and perhaps changes to the terminal buildings as well)

• Reducing the minimum time between takeoffs (for instance by designing aircraft for faster unloading and reloading), or reducing the time between landings (via better air traffic control).

Busier airports require infrastructure serving the airports such as larger car parks, bigger freight terminals, and better interconnection with other modes of transport such as road and rail networks.

3.4.13. Environment Despite the fact that today’s aircraft are 75% quieter than those of 30 years ago and aircraft fuel consumption matches that of modern cars (IATA, 2004), the aerospace industry is under pressure to better understand and mitigate the environmental impact of air transport. Environmental concerns may drive governments to introduce regulations on noise-level and emissions (figure 3.14). As suggested in the previous section, environmental concerns have been the driving force behind the limitation in airport expansions and development, and resistance of communities near airports to increase in the number of aircraft operations (Clarke, 2003).

Aircraftsize

Numberof nightflights

Newairports

Newrunways

Air traffic control

Alternativetransport

Landingcharges

Turnaroundtime

Airportcapacity

Infrastructure serving airports

Aircraftnoise

Environmentalprotection

Passengertraffic

Freighttraffic




Figure 3.14: Factors related to environment Environmental requirements have also been the force for modernisation of aircraft fleet by airlines in the mid- to late- 1990s (Murray, 2003). If this trend continues, aircraft may be retired earlier than usually the case. Environmental awareness may also change the public and passenger attitude to fly. As shown in Appendix 1, ACARE has set several goals with respect to the environment including CO2 and noise reduction by 50%, NOx reduction by 80% and substantial progress towards green Manufacturing, Maintenance and Disposal (MMD). Murray (2003) highlights that in addition to aircraft noise and emissions, the potential polluting effect of MRO facilities as part of airport infrastructure is also increasingly recognised and regulated. IATA, which comprises some 275 member airlines, responds to the environmental challenge by developing policies to minimise the aviation impact on the environment (IATA, 2004). Their policies include a new NOx stringency standard and balanced approach to noise management. They also established night flight policies to co-ordinate airline responses to increasingly stringent operational restrictions at airports, particularly in Europe. IATA opposes the imposition of fuel and so-called environmental taxes and proposes the use of fuel efficient-aircraft as a win-win solution to mitigate the environmental impact of air travel without compromising airline financial health.

Passenger traffic

Demand for energy

CO2 Emission

Taxation

Environment

Manufacturing, Maintenance andDisposal (MMD)

processes

Aircraft retirement

Airport capacity(noise)

NOx Emission

Regulation




3.4.14. Regulation As suggested in the previous sections, regulation is an important issue affecting many aspects of the aerospace industry. Some of these factors are captured in figure 3.15.

Figure 3.15: Factors related to regulation Growing concerns on the environment may introduce regulation to control the environmental impacts of air travel e.g. noise-level and emission. Airport capacity also depends whether the government will allow development of new airports or existing airports. Other aspect of regulation in terms of certification and qualification relates closely to flight safety. Changes to regulations are often precipitated by an incident. As such, it is difficult to predict what new changes might be required in the medium to long term. It should be possible to identify likely remedial actions arising from recent incidents, however. A historical example of a changed procedure would be the requirement that passengers must not be on board an aircraft while it is refuelled. This increases turn-around time, and hence pushes up journey time for long flights, and operator costs. In addition to regulation, there is the possibility of deregulation; allowing new businesses to enter the market as operators, Maintenance Repair Overhauls (MRO) spares manufacturers, etc. Where increased regulation would tend to push up costs in the name of safety and environmental concern, deregulation aims to eliminate constraints where they are not needed, increasing choice and tending to reduce costs for operators and passengers alike. Important aspects of regulation, where changes could drive radical changes in the future of the aerospace industry relate to airline national ownership and agreement on air traffic management. The current ownership restrictions limit cross-country mergers or take-overs. However, in an increasingly competitive airline industry, airline operators need to build up an extensive global network to achieve economies of scope and to meet passenger demand (Oum et al., 2001). Tretheway (2004) argues that as a result of the emergence of new and successful business models such as low-cost carriers, full service network carriers will serve a declining market share. As a consequence, consolidation of network carriers across national frontiers is desirable and necessary.

Certification

Security

Passenger traffic

Regulations

Airport capacity

Air traffic management

Politics

Safety

Deregulations

Alliances




The International Air Transport Association (IATA) clearly stated that they would like to see more ‘business-like environment’ by governments in different regions (Donne, 2004). They are urging government to change the current bilateral system of air traffic to ‘open-skies’ agreements. They also stressed that governments should allow airlines more freedom to merge, acquire and to go to the international financial market. The establishment of a proposal for ‘Trans-Atlantic Common Aviation Area’ (TACA), which would remove the current artificial barriers as to which airlines can or cannot fly between the US and Europe and restrictions on airline ownership rules, will radically alter the structure of global aviation operations (Donne, 2004). In addition to those changes, IATA (2003) also calls for government action that would contribute to financial sustainability by regulating airport and air traffic providers, taking responsibility for security costs and eliminate discriminatory taxes and fees. They also urge the government to develop common standards and harmonise the industry’s regulatory framework.

3.4.15. Passenger attitudes As shown in figure 3.16, passenger needs and preferences certainly affect many aspects of air transport. Boeing (2004a) predicts that many passengers in the future would avoid transits at ‘hub’ airports and would consider non-stop direct flights as they offer more comfort, speed and convenience.

Figure 3.16: Factors related to passenger attitudes

Different values pursued by different types of customers relate closely to the product and service offering from the operators. Changes in passenger attitude can certainly influence the product and service offering from operators and even aerospace manufacturer. Passengers growing concerns on the impact of air travel on the environment may put more pressure to the aerospace industry to be more environmentally friendly. Similarly, passengers concern on

Convenience

Time to destination Safety

HealthComfort

Passenger Attitude

Travel costs

Service offering

Green thinkingPassenger traffic

Security




health, safety and security may affect their willingness to fly. Learmount (2004, p. 13) reports that “passenger health on international flights was formally acknowledged as an integral element of safe air travel” by members of ICAO. Standards applying to passenger health will be reviewed, more research on the subject will be carried out and where required new standards will be created. The ability to understand the passenger needs means that operators can focus on offering service to cater for these needs. Recent trends in the airline industry show that full service network carriers that aim to satisfy the needs of all passengers are struggling to compete with new business models serving specific market segments (Costa et al., 2002; Tretheway, 2004). There is now a growing demand for regional business jets to serve business travellers who generally emphasise frequency of flights and convenience (Costa et. al., 2002). On the other hand, there are also many passengers with the simplest journeys that value cheap tickets. This type of passenger is the target market for low-cost carriers such as Ryanair and EasyJet. These passengers arguably have less need of baggage, and do not desperately need complementary meals and in flight entertainment. Therefore, Ryanair strictly limits the amount of baggage that its passengers can carry and do not offer complimentary meals or in flight service (Tretheway, 2004).

3.4.16. Demographics There are several demographic factors that influence passenger traffic (figure 3.17). These are:

• Population growth. Population growth drives economic activities and becomes a driving force for demand in air travel.

• Improved disposable income in developing countries. Continuous growth in the wealth of developing countries such as China, India and Eastern Europe and air travel is becoming affordable by more and more of their populations. This ensures that air travel worldwide will continue to grow (Airbus, 2003).

• Migration. Even in mature markets such as United States, inward migration is expected to drive demand for air travel as people travel to visit friends and relatives in distant countries (Rolls Royce, 2004).

• Tourism and the desire to acquire knowledge of distant countries and cultures

• Breakdown of political boundaries in large regions such as Europe means it is very easy to travel between countries in this region.

Together, these factors are the major driving forces for continuous growth in air travel.




Figure 3.17: Factors related to demographics

3.4.17. Green technology Factors related to green technology are shown in figure 3.18. In order to meet the challenges of providing an air transport system with little impact on the environment, new and green technology needs to be developed. Research and development activities are crucial for the invention of such technology. Funding the research and development activities will be a major issue and some kind of subsidy may be inevitable. A win-win solution proposed by IATA (2004) to mitigate the impact of air travel on environment is the use of fuel-efficient aircraft. They argued that as cost of fuel form a significant part of airlines operating cost, fuel-efficient aircraft reduce the direct operating costs of the airline and the level of emissions in the atmosphere. They feel that this is a better solution compared to introducing fuel and environmental taxes.

Sehra and Whitlow [2004] describe NASA’s goals for sustainable 21st-century air travel, aimed at producing a vehicle with near-zero harmful emissions; a machine that is highly unlikely to be available for decades. Meanwhile, trends in technology such as increasing bypass ratios and increasing maximum turbine temperatures show how environmental harm might be limited, and fuel consumption reduced, in the interim.

Passenger traffic

Migration

WealthDemographics

Population growth Politicalboundaries

Ageing population




Figure 3.18: Factors related to green technology

3.4.18. Certification Certification is closely related to regulation of the industry (Figure 3.19). This is the means by which technical changes are brought about, forcing the updating or retirement of potentially unsafe equipment, and ensuring that spares are fit for their purpose. Certification for new aircraft or equipment may require lengthy processes. Therefore, certification may influence the development time. Airworthiness certification may lead to certain aircraft types being updated, or removed from fleets, with a corresponding impact upon the manufacture and overhaul businesses. Likewise, Parts Manufacturer Approval (PMA), Supplemental Type Approval (STA) etc. determine the players in the aftermarket sector.

Demand for spares

Taxation

Green Technology

Subsidy

Aircraft fleet

Cost of fuel

Research and development




Figure 3.19: Factors related to certification

3.4.19. Operating costs Operating costs for operators are typically made up of costs of cabin crew and ground personnel, as well as costs of fuel, consumables, insurance, borrowing, maintenance etc. Some of these costs are shown in figure 3.20. The operating costs are affected by exchange rate, taxation and aircraft type. More detailed description on operating costs in the airline industry can be found in Tsai & Kuo (2004). Operating costs are an important factor in the aerospace industry. Airbus (2003) states that the number one driver for air travel demand is the availability of tickets at affordable prices. Therefore, full service airlines are under pressure to cut costs. Many stakeholders in the aerospace industry share this view (ACARE, 2002; Costa et. al., 2002; European Metalworkers Federation, 2003). They believe that the key for long term growth in the aerospace industry is cost reduction. However, there are many challenges to drive down the costs due to increase security costs, fuel costs and inefficiencies in the value chain.

Manufacturers in marketplace

Cost of spares

Certification

Development time

Aircraft fleet

Safety regulation

Retirements




Figure 3.20: Factors related to operating costs

Recent terrorist acts and security threats have forced the aerospace industry to introduce many security counter-measures that come with enormous costs. The implementation of new measures requires airlines to invest in procedures, equipment, personnel and training. According to IATA (2004), airline expenditures for security reached an estimated US$5.6 billion in 2003. The strengthening of oil price, an average of 50% increase in the last two years, is another challenge for the industry to cut costs. Airlines could see 2.5% - 3.5% increase in operating costs, if oil prices remain near May 2004 levels (IATA, 2004). The International Air Transport Association (IATA) argues that while the airline industry continue to introduce their own part in cost cutting, support from the governments and commercial partners are essential. The airlines pay an annual bill of US$40 billion for user charges. Airport and air navigation service charges represent about 10% of airline operational costs. As many providers are monopolies, there is a lack of competitive pressure on airports and other suppliers of aeronautical services. IATA is urging governments to provide regulation to ensure open and transparent charging practices. In order to drive down the cost of the entire value chain, a new order is needed to replace the current ‘cost-plus’ pricing.

3.4.20. Cost of financial services

Wage bill

Cost of insurance

Exchangerate

Level ofoperator

debt

Cost ofmaintenance

Operating costs

Cost ofconsumables

Airline revenue

Aircraft type

Cost of fuel

Cost ofborrowing

Taxation




The cost of financial services is an important influence to most industries as it affects revenue. It affects the aerospace industry greatly because of a great proportion of money used to fund expensive development project comes from banks. Therefore, the interest rate can be a major issue, albeit short term, for many players in the aerospace industry. For example, dramatic drop in interest rate in September 2003 has to some extent caused higher losses at Delta Airlines (Bond, 2003).

Figure 3.21: Factors related to costs of financial services

In the wake of recent external shocks such as 11/9 terrorist attack and the war in Iraq, the cost of insurance has also become a major concern to the airline industry. Margo (2002) states that the provision of proper coverage in respect of the risks of war, terrorism, and related perils by traditional markets at affordable rates is critical to the operation of the world’s airlines.

3.4.21. Cost of fuel Jet fuel (or kerosene) is a light hydrocarbon, and as such is an expensive commodity. The price is dependent upon factors such as demand for energy, the output of crude oil, and perhaps in the future, taxation. According to John Heimlich, Chief Economist of Air Transport Association, fuel expense remains the airlines’ second largest operating expense (figure 3.22). Thus, high fuel prices always have a significant impact on the industry (Air Transport Association, 2004a). The President and CEO of Air Transport Association emphasised further “every penny increase in the price of jet fuel costs the airline industry $180 million a year” (Air Transport Association, 2003c).

Costs of FinancialServices

Airline revenue

Size of debts Interest rate




Figure 3.22: Factors related to cost of fuel

The increasing scarcity of fuel is having an impact upon the design of aircraft, with faster aircraft designs such as Boeing’s Sonic Cruiser being shelved (as the American SST, the Boeing 2707, had been in the early 70’s). The aircraft that the operators now want are those with the lowest possible operating costs, with fuel being a major element of the cost of a passenger kilometre. Aircraft are a fuel-efficient form of travel. A 747 uses approximately 150,000 litres of fuel in a ten-hour flight, or 12 litres per kilometre flown (figures from Boeing). In the ‘miles per gallon’ format that British motorists will be more familiar with, this is in the region of 100 miles per gallon per person – at 550 miles per hour. Of course, fuel usage is not the only contributor to environmental harm.

3.4.22. Ticket price Ticket price depends upon many factors as shown in figure 3.23. Typically, operators determine ticket price based on distance, seasonal activities and age of passenger. It is quite common that long-haul flight and peak season tickets to be more expensive than short-haul and off peak tickets. Airlines also charge children differently. In addition, ticket price is influenced by the passenger demand, the operator capacity and costs and new entrants. The practices of differential pricing and yield management have been used by most airlines in order to maximise their revenue (Belobaba and Wilson, 1997). Airlines recognise that different types of passenger have different sensitivities to price. It is known that business passengers are less sensitive to price compared to leisure passengers (Brons et. al., 2002). Thus, in order to segment the total demand for air travel according to sensitivities to price and the need for travel flexibility of business and leisure passengers, airlines typically offer a range of fare options at different price levels on the same flight. Yield management system is discussed further in the next section.

Politics

Cost of fuel

Operating costs

Demand for energy




Figure 3.23: Factors related to ticket price

Despite their attempt to sell tickets to achieve profitable margin, the operators sometimes change price of a ticket to meet certain purposes. For example, following external shocks such as the 9/11 terrorist attack, SARS virus, and wars in Afghanistan and Iraq, many airlines were forced to cut their price in order to attract passenger and fill the seats. Price can be used by the authority to control the aviation industry (Brons et al., 2002). For example, governments can control price to reduce the negative effect of aviation on the environment. However, the authorities need to understand the price elasticities of passenger demand i.e. passenger sensitivity to price changes in order to justify the impact of policy changes. If extra costs are added for passengers without decreasing demand, such policies will have little effect.

3.4.23. Yield Figure 3.24 shows that operator yield comes from selling tickets to passengers. Yield varies according to the service offering. Business passenger typically brings higher yield compared to leisure passengers. Yield is also highly determined by the yield management approaches that operators use, airline frequency and flight schedule placement in the market. Yield management systems are used by the airlines to forecast demand and calculate the number of seats to be made available for each fare type in order maximise total flight revenues (Belobaba and Wilson, 1997). However, they argue that even the best yield management can not overcome major schedule disadvantages.

GDP

Price of ticket

Airline capacity

Yield

Airline costsPassenger

attitude

Passenger demand

New operators




Figure 3.24: Factors related to yield

3.4.24. Operator revenue Operator revenue is determined by yield and operating costs (Figure 3.25). Airline revenue or profitability, in turns, influences their ability to buy new aircraft for fleet expansion or replacing old aircraft.

Figure 3.25: Factors related to operator revenue

Airline revenue may increase with the use of yield management systems. Belobaba and Wilson (1997) summarise from previous study that revenue gains of the order of 2 – 5% are commonly quoted for an airline that implements a basic yield management forecasting and optimisation system compared to the use of no yield management tools at all. They reported further that there is a substantial advantage for ‘first mover’ airline that initiate yield management first in a competitive market. They claimed that such airlines could gain revenue from carrying a better fare mix of traffic and from protecting seats for late-booking, high-fare passengers.

Operating costsOperator Revenue

Yield


Number of passengers

YieldAirline revenue

Service offering

Price of tickets

Distance




3.4.25. Product and service offering Lindstadt and Fauser (2004) classify typical airline products into four major products:

• Inter-continent product

• Premium continental product

• Standard product

• Low cost product Each product is typically associated with a certain level of services to satisfy different passenger needs. For example, premium continental products focus on fast and convenient pre- and after-flight services on the ground (e.g. late check-in, quick security check etc) and less on onboard ‘frills’ such as entertainment or top quality foods. This means that product and service offering relate closely to costs. Product and service offered by an operator depends on their aircraft fleet. Some factors related to product and service offering are depicted in figure 3.26.

Figure 3.26: Factors related to product and service offering In the long term, energy availability and green thinking may influence products manufactured by aerospace manufacturer. As mentioned previously, the scarcity and price of fuel means operators may order more fuel efficient aircraft.

3.4.26. Aircraft fleet Aircraft fleet is influenced by retirements of old aircraft, deliveries of new aircraft, new aircraft prices and aircraft return from storage (Figure 3.27). It is also influenced by airline business

Certification

Demographics

Passengerattitude

Product and Service offering

Green technology

Costs

Service offering

Aircraft fleet

Energy availability

Load factor




models. According to Costa et al (2002), the emergence of new airline business models emphasising low cost and more convenient offerings means that:

• The mix of aircraft being ordered will change

• More planes being sold to the low fare, high utilisation carriers and to regional and business-jet operators.

If the airline business model remains substantially the same as it is today, then the manufacturers may have to accept lower overall demand for new aircraft not only during the cyclical downturn but also as an industry norm. In this case, purchases will focus more on replacement aircraft rather than on fleet expansion.

Figure 3.27: Factors related to aircraft fleet

The existing aircraft fleet will determine orders for new aircraft and product and service offering of the operators. ACARE predicts that in the year 2020+, the aircraft fleet will consist of a greater proportion of large aircraft and larger fleets for freight transportation. Airbus appears to share the same view. Their recent market prediction shows larger proportion of large aircraft compared to Boeing. Over the total demand for new aircraft, Airbus (2003) predicts a higher demand of very large aircraft (1535 units) such as A-380, compared to Boeing (2004a) that predicts only 910 units. ACARE also assumes that passenger and fleet transport will be more separated to optimise their respective cost operations.

3.4.27. Aircraft retirement Aircraft retirement depends upon age and aircraft usage measured by number of passenger and distance they fly (Figure 3.28). Aircraft retirement relates closely to aircraft fleet and demand for new aircraft. Airlines buy new aircraft not only to meet traffic growth but also to

New aircraft

Aircraft fleet

Retirements

Aircraft in storage

Aircraft return from storage

Product & service offering

Orders for new aircraft

New aircraft prices




replace their older aircraft, as they tend to be noisier and less efficient. With growing concerns over the environmental impact of air travel, more aircraft are retired early.

Figure 3.28: Factors related to aircraft retirements

Airbus (2003) states that during the period 2003 – 2022, airlines will retire approximately 40% of the current active fleet. They predict that 4,914 of passenger and cargo jets will be retired. Rolls Royce (2004) predicts a similar figure. Boeing’s (2004a) prediction is slightly higher. Over their 20-year forecast period, they predict around 6,400 airplanes will be retired.

3.4.28. Demand for new aircraft Demand for new aircraft depends upon the profitability of operators. As highlighted by Aerospace Innovation Growth Team (2003), prolonged financial distress experienced by world major operators will affect their ability to buy new equipment in the medium term. Predicting demand for new aircraft is a common process that is done continuously by key players in the aerospace industry. Typical processes to predict demand conducted by Rolls Royce and Volvo Aero Corporation have been discussed in section 2.2. Additional information may be obtained from publications provided by Boeing (2004a, 2004b) and Airbus (2003). Based on these sources, several factors generally considered by the key players in predicting the demand for new aircraft are identified; traffic growth, load factors, aircraft utilisation, aircraft fleet and aircraft retirements. This is shown in figure 3.29.

Aircraft retirements

Certification

Aircraft fleet

Distance

Number of passenger






Figure 3.29: Factors related to demand for new aircraft

Boeing (2004a) predicts that in the next 20 years there will be demand for 25,000 new commercial airplanes, Airbus (2003) predict that nearly 16,500 new aircraft will be delivered, and Rolls Royce anticipate a market of approximately 41,000 new aircraft. These are not as contradictory as they appear at first glance, since each of these forecasts is based upon the market segments where the company has a suitable airframe or engine product. A significant part of the discrepancy comes from the market for business jets, which may represent around a third of the total.

3.4.29. Demand for maintenance Maintenance activities are an important part of airworthiness. According to Wu et al. (2004) “aircraft maintenance is actions that can restore an item to a serviceable condition, and consist of servicing, repair, modification, overhaul, inspection and determination of condition”. They differentiate aircraft maintenance as corrective or unscheduled maintenance and preventive maintenance or scheduled maintenance. Preventive maintenance is done at defined or scheduled intervals in an aircraft and equipment’s life to make sure that they remain in a serviceable condition. When attempts to restore an item to satisfactory condition fail, corrective maintenance is performed by providing correction of a known or suspect malfunction and or defect. Wu et al. (2004) highlight several factors specific to a particular airline that may influence maintenance activities such as location of the operator, fleet size and commonality, aircraft age and utilisation, frequency of check intervals, etc. Aircraft utilisation is determined by passenger and traffic. Demand for maintenance for an individual aircraft depends upon a number of factors such as intervals of flying hours, elapsed time, and number of cycles i.e. landings, full power take off, etc. Some of these factors are captured in figure 3.30.

Number ofPassenger


Retirements

Aircraft fleetDistance

Operators revenue

Safety




Figure 3.30: Factors related to demand for maintenance Komorowski (2004) proposed a comprehensive set of tools for pro-active maintenance of aircraft structures that are attractive for economic and safety reasons. However, he predicts that the transition of these new tools to the maintenance, repair and overhaul (MRO) industry will be challenging because the industry is heavily regulated, unaccustomed to radical change and dominated by OEM prescribed solution.

3.4.30. Cost of maintenance Wu et al. (2004) states that maintenance costs of commercial aircraft contribute significantly to an aircraft’s cost of ownership and eventually operating costs (Figure 3.31). According to them, direct maintenance costs i.e. labour and material costs directly expended in performing maintenance of an aircraft or related equipment, are influenced by several factors including design of the aircraft, fault diagnosis efficiency, organisation-related variables and environmental factors. Their research propose a new concept of reliability and maintainability design called Maintenance Free Operating Period (MFOP) and fault diagnosis expert system as ways to reduce direct maintenance cost. As reported in Business and Commercial Aviation (2003), Maintenance Cost Control Programs are designed to provide flight department managers with predictable costs based on the department’s specific flight activity. They aim to help flight department managers to budget maintenance realistically. The maintenance plan providers typically present standardised maintenance pricing based on: 1. Annual flight hours, 2) annual landings, 3) operating environment which include home airport, storage, maintenance and operation, 4) contract, 5) mission and 6) aircraft.

Aircraft retirement


Aircraft fleet Passenger traffic

Freight traffic




Figure 3.31: Factors related to cost of maintenance

3.4.31. Air traffic management Air traffic management is another important issue highlighted by ACARE (2002). As suggested in the previous section, the way in which the air transport system is managed may limit the number of flights and constrains the air transport ability to cope with traffic. It is also related closely to safety. Factors related to air traffic management are shown in figure 3.32. Air transport management is potentially affected by political issues. For example, at present, flying rights between individual EU member states and the US are governed through bilateral agreements (Aircraft Economics, 2003). Many stakeholders in the aerospace industry are urging the government to change the current regulation on air traffic management. This means that the current bilateral system of air traffic agreements will give way to regional ‘wide-open skies; wherever governments considered it feasible (Donne, 2004). Air traffic control has been highlighted by the airline industry as sources of inefficiencies. President of Association of European Airlines argues that the airline industry suffers from uneconomic routings and needless holding patterns due to inefficient traffic control (Flight international, 2004, p. 10). He argues further that inadequate air traffic control contribute to congestion leading to unnecessary delays and longer journey time. The old-fashioned air traffic system also means that the airline has to waste a lot of fuel to fly the patterns.

Cost ofspares

Cost ofMaintenance

Cost of labour

Servicecontract type

Aircraftfleet

Supplementaltype approvals

Operating Costs




Figure 3.32: Factors related to air traffic management

3.5. REVIEW PROCESS FOR THE FACTORS MAPS Since a detailed understanding of the factors influencing the aerospace industry is at the core of WP 2.1.1, the factors mapping process includes a phase during which feedback is to be sought. That process is now underway, and may lead to additional factors, or reviews, trends, inter-relationships being incorporated into the map during a second phase. A map showing the factors in the first and second tier was produced, together with some introductory text. This was circulated to partner organisations, together with a questionnaire. Questions asked included.

• Is the factors map a good way to describe the business environment?

• Are any factors missing from the map? (If so, please add them to the diagrams where appropriate.)

• Can you identify the factors and interrelationships (arrows) that are of critical importance? (Circle the most important influences; these will be the focus of attention in future modelling work.)

• Should some of the factors be combined? Identify those that might be merged.

• Can you describe any trends in the factors that fall within your area of expertise?

• Can you provide any other comments that would improve the maps that are presented within this document?

RegulationAir trafficmanagement

Politics

SafetyJourney time

Number of flights




3.5.1. Initial Feedback on the Factors Maps Here we include a brief summary of responses from reviewers. VAC staff who acted as reviewers included a market & sales manager, a market analyst, a project leader and the market director for military programmes; at UNOTT a member of staff who is principal investigator on another VIVACE project (WP2.5) also participated in the process. The feedback is in general very good on the factors map. All the contributors have commented that the work is done on a detail level that is considerably better then comparable work in the industry. The main purpose for sending out the factors map was to get answers on several questions. We will here put the light on some of the feedback. Is the factors map a good way to describe the business environment? All the contributors think that this is a good way to present the business environment, but the current version is too complicated, and we need to focus on a smaller number of factor or at least group the factors. And that is exactly the reaction we wanted. Because of the feedback we have got, we are now better prepared to decrease the numbers of factors. Are any factors missing from the map? (If so, please add them to the diagrams where appropriate.) There are different comments around factors on different levels, and we don’t think it is necessary to go trough everything here. The only two factor that has been added on the top level is “large companies travelling policy”, and “alternative transportation solutions”. Some people believe that these two factors are very important for the business, and of course will we look in to that. Can you identify the factors and interrelationships (arrows) that are of critical importance? (Circle the most important influences; these will be the focus of attention in future modelling work.) The factors that come up in this question are: GDP, traffic growth, yield, environment and passenger attitude. And that the interrelationships between GDP, traffic growth and yield are extremely important. This is exactly the feedback we were looking for, so we could start the work to exclude many factors and focus on considerable fewer factors. Should some of the factors be combined? Identify those that might be merged. Most of the contributors wanted a simpler model, in short that we grouped or merge some of the factors together, but nobody was capable to give example or do it themselves. And we believe that we here we have the real problem. How do we sort out, group or merge the factors map in a way that we will get a reasonable number of factors to work with? Can you describe any trends in the factors that fall within your area of expertise? If we should summarise the feedback on this question we have to look in to five factors. Yield will decrease, Aircraft demand will increase, aircraft fleet will restructure, service offering will go to low cost airlines and environmental factors will be more important. Can you provide any other comments that would improve the maps that are presented within this document? The general feedback is that we should focus on some (maybe 10-15) factors and their interrelationship. The feedback received so far has been very useful for us, and perhaps more important is that we have created contacts with several peoples and competencies within the industry that we can use in the future to develop the factors map, our knowledge and the future models.




3.5.2. Invitation for Further Feedback Feedback on the factors presented in this chapter from other partners is currently being sought, with the aim of producing a final consensus factors map early in the next phase of VIVACE.

3.6. CONCLUSIONS An extensive literature review and analysis has been conducted, identifying a large number of issues that exert some influence on operators, manufacturers and/or suppliers of supporting services. These were combined into a consensus map, using a two-tier format to avoid information overload. At the time of writing, the results are being validated, in order to further enhance the map. It is anticipated that a revised version of factors map will be released subsequently. Having researched, identified and understood a set of principal aerospace industry factors, initial business scenarios could be constructed, as described in the chapter that follows.




4. CHAPTER 4: INITIAL FUTURE BUSINESS SCENARIOS

4.1. INTRODUCTION The factors map described in the previous section was used as a reference to identify key drivers, in terms of importance and uncertainty, which shape the future business environment. This chapter explains the process by which key factors were expressed as a range of initial business scenarios, to be presented within a software tool that would allow the user to generate a theme that represented a possible future.

4.2. SELECTION OF SCENARIO MODELLING METHODOLOGY

The aerospace business environment is clearly a highly complex one, and to oversimplify it would be to produce a model with only limited relevance in the real world. At the other extreme, attempting to produce a model that takes into account the dozens of industry factors presented in Chapter 3 would be to create a system of complex interactions that it would be almost impossible to validate.

In seeking a methodology where alternative future aerospace business environments could be defined, it was identified that the key drivers fell into two distinct categories:

• External factors that acted upon the enterprise, and

• Internal factors, selected as responses to the business environment.

An example of an external factor might be a piece of legislation imposing further limits on aircraft noise. Responses depend upon the business under consideration. The manufacturer of aircraft engines might choose to pursue a long-term technical solution, the MRO business might anticipate an increase in activity, fitting ‘hush kits’ to older engines, and the operator may have to consider changes to routes, timetables or the aircraft fleet.

The responses of businesses within the aerospace value chain are driven by the external environment, but attempting to construct a model in such a way that a given set of circumstances triggers the response is unnecessary. By adopting a methodology that employs the two distinct phases of considering external and internal factors, a great deal of complexity can be removed from the model (with a corresponding reduction in the likelihood of error).

Section 4.3 presents a methodology by which the aerospace business environment may be described. It includes nineteen ‘dimensions’, each explained through the use of a pair of hypothetical, diverse scenarios. Figure 4.1 illustrates an example:




Figure 4.1: Sample ‘dimension’ for the description of a future aerospace business environment

Considered in isolation, each dimension allows one aspect of the future to be plotted. In every case, however, a change to the scenario under study could well be accompanied by changes in others.

An initial core of eight dimensions has now grown to a total of nineteen - See Section 4.3. (Following a feedback phase, the set of dimensions may grow further, although rate at which new issues are added appears to have slowed.) Fortunately, not all businesses within the value chain are affected by every potential change, so the complexity of exploring future business scenario permutations is further reduced.

4.3. INITIAL BUSINESS SCENARIO DIMENSIONS If we are to discuss the future aerospace business environment, it is first necessary to distinguish between external influences and internal ones. As we move forward in time it is reasonable to expect that many factors will change, but a distinction must be drawn between those that act upon the businesses in the aerospace value chain, and those that are responses. For example, legislation that requires that aero engine noise emissions are reduced is an external influence; the technical responses to this challenge by engine manufacturers, and the financial implications of a forced move to quieter engines, reduced levels of operation at airports, etc. are responses, and must be considered separately. In accordance with the best practice guidelines identified in Chapter 2, all scenarios are paired, not attempting to predict a future outcome but rather simultaneously exploring an increase or decrease in any factor. On this basis, nineteen pairs of scenarios have been selected for inclusion, each described in the subsections that follow. Figure 4.2 shows the scenarios that have been identified to date:




Figure 4.2: Initial business environment scenarios The subsections that follow describe each of these nineteen scenarios in detail.

4.3.1. Hub Airports vs. Direct Flights This scenario considers changes that operators might make to the routes on which they operate scheduled flights in the future. Routing flights through major ‘hub’ airports allows economies of scale, and hence cost savings that may well reach the customer. However, some passengers may find that their journeys are made longer and more complicated by the need to fly via one or more hubs. Alternative A: The Hub Society In this scenario, operators pursue economies of scale by routing flights via selected nodes. Economics, plus limitations to the expansion of well-known airports that have now been enveloped by housing, may mean that the super-hubs of the future are sited in remote areas. The aircraft used to fly between the hubs are large, and they fly frequently. Such a structured offering is simple to scale, so there are few empty seats on these services. This simplicity reduces variability, so schedule adherence is better. Smaller aircraft – or other transport solutions – carry people to and from the hub airports. Some of these secondary routes require very small aircraft, or infrequent flights. Intercontinental services tend to depart from hubs. In areas with a high population density, hubs may be complemented by infrastructure developments such as motorways and railway services. Otherwise, a journey may involve several flights. Alternative B: The Point-to-Point Society In this scenario, customers eschew hubs, demanding instead to be taken direct from a reasonably close airport, to an airport close to their final destination. This probably involves a higher ticket price than the hub option, but has the benefit of reducing the total time in transit, and reducing uncertainty, journey planning and baggage-handling difficulties. Large aircraft are less useful in this role, since it is difficult to find enough people wishing to make the same




journey at the same time. Instead, there is a growth in the demand for medium-sized aircraft with relatively long range. Under this alternative air traffic control is much more complex, with lots of relatively small airports being used. There may also be an increase in the demand for flight crews. This pair of alternatives is associated with the following:

• Scenario 4: Airport Availability, since runways or new airports may allow different journeys.

• Scenario 6: Journey Length, since hubs may be used for longer journeys while being fed by smaller aircraft, travelling relatively short distances, from secondary airports.

• Scenario 19: Freight Activity, since freight demand patterns may make a strong business case for or against the use of hubs, depending on the volume of freight carried on passenger aircraft on each route.

4.3.2. Aircraft age In contrast with many other manufactured products, aircraft are designed to have a very long service life. The safety-critical nature of aviation, and exacting performance requirements have produced systems that can be expected to remain in service (with some mid-life upgrades) for up to 40 years. Of course, older aircraft may not be popular with passengers, and they may be superseded by aircraft with lower operating costs, etc. Alternative A: Ageing Aircraft In this scenario, growth in air travel is achieved only at the expense of a downward trend in the price of a ticket. Seeking to retain market share and remain profitable, operators tend to operate existing aircraft for longer, and to enlarge their fleets by purchasing used aircraft from other regions, or returning aircraft to service from long-term storage. New aircraft may be introduced on some routes, but they are ordered in relatively small numbers. Older aircraft fly between less popular city pairs. The average age of aircraft in the fleet increases as a result. Safety may ultimately suffer, and operating costs are higher, since older airframes and engines are likely to be approaching a major overhaul. They also tend to be less fuel-efficient. (Against this, the initial investment for the fleet owner is lower.) The environment is harmed by pollution, including increased noise, but people become increasingly accustomed to cut-price air travel. Alternative B: New Aeroplanes Legislation, or perhaps public reaction to accidents or environmental problems, demands that aircraft are replaced sooner. Overall, the primes experience an increase in orders, though operator loyalties to a particular aircraft manufacturer may change. The demand for spares is reduced, since aircraft are replaced outright at an earlier stage. Heavy discounting, in the hope of recovering the money in the aftermarket phase, has to cease. Naturally, the cost of air travel increases. Demand for fuel might be expected to fall, though aircraft retired in the developed world may find their way overseas, to live out their original design life.




As an interim measure, MRO businesses fit mid-life upgrades that are meant to reduce noise, increase safety, or perhaps improving aircraft by fitting more fuel-efficient engines, blended winglets, etc. to reduce fuel consumption. Individual countries or regions may lead the way, banning certain aircraft types from their airports or airspace, or requiring that certain pieces of equipment are carried. This pair of alternatives is associated with the following:

• Scenario 5: Quality of Service, since newer aircraft may offer greater comfort. • Scenario 11: Environmental Issues, since older aircraft to cause more harm. • Scenario 19: Freight Activity, since at present it is common for older aircraft to be

converted into freighters.

4.3.3. Operator Partnerships Alliances between carriers become possible when the airline market in a region is deregulated to some degree. Wang et al [2004] reported that alliances tend to increase market share and seat occupancy levels; the authors propose a five-level taxonomy of strategic alliances:

• Bilateral form • Code share • Joint activities • Marketing alliance • Open skies

This scenario investigates the extent to which operators collaborate in the future, both in terms of the number of routes shared and the level of integration desired within the partnership. Alternative A: Alphabet Soup In this scenario, ‘Open Skies’ de-regulation permits operators to provide services jointly. Various levels of collaboration are possible, but the net result is that passengers who may have booked with two or more airlines share the same aircraft. Sharing flights permits larger aircraft to be operated, and higher efficiency in terms of seat occupancy. This economy of scale increases yield, and may reduce the cost of tickets. Unless the fall in prices prompts an increase in the number of journeys made, travellers may well find that future schedules offer them less flexibility, since there are less actual flights being operated. For the same reason, the demand for MRO services is reduced. Fuel usage may also fall.




Alternative B: Single Operator Routes Reluctant to share revenue and dilute their brand image, operators do not collaborate as above. In the short term, ticket prices are slashed in an effort to improve seat occupancy and maintain market share. (Prices will rise once competitors have been driven away.) New destinations are opened up by operators that find the competition for key city pairs too stiff. They are unlikely to return to the fray later, since scarce slots at major airports will have been surrendered. This pair of alternatives is associated with the following:

• Scenario 1: Hub Airports vs. Direct Flights, since alliances may influence the routes that are operated.

• Scenario 4: Airport Availability, since alliances may allow access to previously unavailable destinations.

• Scenario 10: East and West, since alliances may represent a means of investment in new markets.

• Scenario 18: Business Start-ups, since alliances may offer a means for smaller businesses to enter the market.

• Scenario 19: Freight Activity, since alliances may involve moving freight as well as (or instead of) passengers.

4.3.4. Airport Availability One of the key constraints to growth in air travel is airport capacity. While jet travel is essential for many businesses and increasingly popular with holidaymakers, few people want to live near an airport boundary. The greatest source of objection to airport construction or expansion is noise. (Additional objections include the loss of greenfield sites, impact upon local infrastructure, and a recognition that air travel in general is harmful to the environment.) Although developments in aircraft engines are leading to products (and mid-life upgrades) that emit less noise for a given amount of thrust, resistance to runways will continue. Measures of airport capacity are typically expressed in MPPA; million passengers per annum, though this is a simplification. The number of runways available affects the throughput that can be achieved at peak times, while the length of runways (and the configuration of parking bays and terminal bays) may place a limitation upon maximum aircraft size. Furthermore, noise restrictions may also limit the size of aircraft, or the number of takeoffs permitted, which may vary with the time of day… The result is a complex geopolitical landscape in which the future expansion of airports remains open to doubt. Alternative A: The Concrete Ceiling – Boats, Trains and Automobiles Although demand for air travel continues to increase, legislators and activists do not permit the development of additional airport capacity. Some or all of the following are constrained: New airports, new runways, higher noise limits, greater night flights. The price of a ticket is likely to increase, since demand outstrips the supply of air travel capability in the affected country (or countries). Few solutions present themselves, though the aircraft being operated from some airports may be replaced by larger ones. (This depends upon runway size, and the nature of the constraint, e.g. number of flights, or total noise level.)




Ultimately, the ‘concrete ceiling’ causes an increase in other types of journey, including rail and sea travel – perhaps to reach a country where airports still have capacity. Considerable investment in infrastructure may be required. Alternative B: Airport Proliferation Faced with growing demand for air travel, legislators permit existing airports to be expanded, and allow new ones to be built. (Ex-military sites from the Cold War are a likely option.) Passenger numbers continue to rise, but congestion in the skies is a constraint, particularly over mainland Europe. It should be remembered that congestion in the skies is not necessarily the result of a high take-up of air travel in the country that is being overflown. Many countries have a very high level of activity in their skies despite being neither point of origin nor destination. More aircraft are built, and existing aircraft options grow in value. Fuel prices increase, since demand outstrips supply. This pair of alternatives is associated with the following:

• Scenario 1: Hub Airports vs. Direct Flights, since direct flights between relatively minor city pairs may be necessary to alleviate pressure on overcrowded major airports.

• Scenario 7: Conflict, since decommissioned military airbases are prime candidates for conversion to regional airports.

• Scenario 11: Environmental Issues, since these may be the driver of constraints (i.e. noise restrictions).

• Scenario 14: Private Aviation, since overcrowded airports and overcrowded skies may force new restrictions on the operators of lights aircraft.

• Scenario 19: Freight Activity, since growth in airfreight requires additional space in the skies and at the airports, just as growth in passenger numbers does.

4.3.5. Quality of service One measure upon which some operators may choose to compete is in the (apparent) quality of their offerings. This scenario explores the possibility that future flights might be increasingly presented as a luxury… or in the opposite strategy, as a ‘bargain basement’ form of travel. Alternative A: The Customer is King In this scenario, an increasingly well-informed population comes to expect a better standard of service from the operators. People who travel business class when working dislike using economy-class air travel with their families, and seek a compromise. Media attention on the dangers of deep vein thrombosis and the like may also cause passengers to demand better seating and more space, while another driver for a better standard of service might be legislation that requires a high level of compensation for delays, cancellations, lost luggage, etc. The price of a ticket increases; even so, some operators face a steep learning curve before they can compete effectively. The number of seats available on each aircraft is reduced as passengers come to expect more legroom, particularly on long-haul flights. Other bases for competition between operators include the quality of in-flight food, departure and arrival lounge facilities, in-flight entertainment, and reduced journey time. (Though existing aircraft




cannot really be flown much faster, there exists a great deal of potential to reduce journey time through efficient passenger and baggage processing. In the long term, transonic and supersonic aircraft may make another appearance.) Alternative B: The Customer is a Pauper Continuing to see the low-cost airlines declaring profits while their own losses mount, the major operators move downmarket, expanding their low-cost operations at the expense of premium services. More aircraft are reconfigured to carry a single-class seating arrangement, and facilities such as galleys are reduced in scale as part of the process. The number of cabin crew is cut to the minimum allowable by law. Competition is conducted almost solely on price, and routes are determined to a large extent by landing fees and passenger departure taxes, since these represent a relatively larger part of the cost of budget travel. New aircraft are ordered primarily with the goal of reducing operating costs; aircraft with luxurious configurations are less useful. This pair of alternatives is associated with the following:

• Scenario 1: Hub Airports vs. Direct Flights, since direct flights should mean spending less time in transit, and a more enjoyable experience as a result.

• Scenario 2: Aircraft Age, since newer aircraft may have a quieter cabin, or offer a smoother ride. (Issues such as aircraft seating are not considered to be a direct result of aircraft age, since these can easily be updated.)

• Scenario 16: Size of Payload, since a generous baggage allowance would be associated with a higher quality of service from the airline.

4.3.6. Journey Length While passenger activity in terms of the number of journeys per annum is the subject of many forecasts, the typical distance flown must also be considered. Journey length determines the type of aircraft most suited to making the journey, and hence a change in flying habits will influence the number of aircraft of each type that are required, and hence the demand for associated products and services such as spares and maintenance. The relationship between total distance flown and metrics such as safety or maintenance requirements is more complex than might initially be suspected. Since the most dangerous phase of any commercial flight is the takeoff, an increase in total kilometres flown does not directly indicate increased risk. Similarly, many required maintenance activities are based upon cycles, the additional wear and tear of slightly longer flights (fuel permitting) being insignificant. Subsequently, it may be necessary to examine the distances passengers and freight fly in more detail, identifying the relative distribution of short hops and longer journeys, and perhaps also identifying flights that are undertaken to feed large hub airports. Alternative A: The Long-Haul Society In this scenario, customers who are becoming increasingly familiar with air travel begin to take more ambitious holidays. Faced with an increasing level of commonality with




neighbouring countries, intercontinental travel is seen as much more exciting than merely international travel. For business travellers, globalisation means an increasing number of journeys to destinations such as the Far East. The cost of these longer journeys is naturally higher, but holidaying passengers may come to take a single, long holiday rather than several short trips. Low-cost airlines struggle to compete, unless they can enter the intercontinental market with suitable long-haul aircraft. The level of MRO work being undertaken is reduced somewhat, particularly maintenance activities related to the number of cycles rather than kilometres flown. Alternative B: The Short Hop Society Passenger growth occurs primarily on relatively short flights, such as between the nations of the recently enlarged European Union. Becoming increasingly accustomed to affordable air travel, the public choose to take lots of short holidays and weekend breaks. Customers taking very short holidays resent spending several hours waiting for their flight after check-in, since this represents a considerable fraction of the total trip. One route to competitive advantage for operators may lie in streamlining passenger processing activities (although in this case airport shopping could suffer). Large aircraft are less attractive to operators, since full occupancy is harder to achieve on many routes, and turnaround times are higher. For aircraft operated on a short hop basis, the increased cycles of multiple short journeys wear out airframes and engines at a faster rate. Both MRO outfits and manufacturers can expect an increase in business volume under this scenario. This pair of alternatives is associated with the following:

• Scenario 1: Hub Airports vs. Direct Flights, since direct flights may well be longer than those involving one or more hubs.

• Scenario 2: Aircraft Age, since a requirement to operate aircraft over different ranges is likely to affect the economic case for their replacement.

• Scenario 8: Fuel Availability, since surcharges to reflect high fuel prices are most noticeable on long-haul flights.

• Scenario 11: Environmental Issues, since multiple, short flights cause much more noise and low-level pollution than a single, long flight.

• Scenario 14: Private Aviation, since a privately-owned or leased aircraft can be used for short-range journeys.

• Scenario 17: Product Variety, since differing requirements for payload and range give rise to an increased number of aircraft variants.

• Scenario 19: Freight Activity, since as with passengers, growth in the airfreight sector may refer to short or long-distance journeys.

4.3.7. War and Peace Since the earliest days, military purposes have been at the forefront of many of the developments in the aerospace sector. While new technologies often spin off into the civil sector, and most aerospace manufacturers have both civil and defence divisions, a world in




which there is widespread conflict is likely to be harmful to the development of a sustainable air transport system, as this scenario describes. Alternative A: Conflict In this scenario, international relations continue to deteriorate, perhaps as a result of the proliferation of weapons of mass destruction. Although a ‘third world war’ scenario remains extremely unlikely in the years to 2020, efforts to influence the governments of newly nuclear-equipped nations could lead to smaller conflicts. International travel would suffer in several ways. Civil airliners would need to make wide detours to avoid an increasing number of trouble spots, and all flights would require further increased security to reduce the likelihood of terrorism. Passenger confidence would plummet, causing a reduction in travel, while oil (and hence fuel) prices could increase to unprecedented levels if the countries affected are major oil exporters. If a long period of conflict (or tension) was experienced, aerospace manufacturers could be presented with opportunities to produce military hardware, including militarised versions of aircraft and engines that began as civil aviation products. (Boeing’s new 737-derived maritime patrol aircraft is an example.) Alternative B: Swords to Ploughshares A lengthy period of peace and prosperity could see oil prices stabilise, though a counter-argument is that the cost of oil is unlikely to fall since a general increase in wealth increases the worldwide demand for manufactured goods and global travel (including freight). The variety of journeys could increase, as destinations that have been inadvisable for travellers become safe again. Demilitarised airbases in NATO and former Warsaw Pact countries could offer a new generation of airports, given sufficient investment. (Even greater inward investment in infrastructure would be required in war-torn countries.) New products or variants may be seen, as defence contractors attempt to play a part in the civil sector. Small business jets might be feasible products for facilities that have previously made warplanes, but some manufacturers will find peacetime a difficult proposition, and ultimately innovation would be slowed, since many of the developments that have led to improved safety in civil aviation originated in the military. This pair of alternatives is associated with the following:

• Scenario 4: Airport Availability, since decommissioned military airbases are a common site for new airports.

• Scenario 6: Journey Length, since the existence of ‘rogue states’ forces detours to be flown.

• Scenario 8: Fuel Availability, since the supply of oil has tended to be disrupted during recent conflicts.

4.3.8. Fuel Availability Gas turbines burn kerosene in large quantities; a Boeing 747-400 has a maximum fuel capacity of 216,319 litres, or 173 tonnes, and will use almost all of this in a fourteen-hour flight. As increasing prosperity brings about growth in passenger demand in many countries, coupled with greater manufacturing and freight activity, fuel shortages may become a problem.




Although oil is normally thought of as a fuel commodity it has many uses in the modern world, not all of which involve combustion; it is also used in the manufacture of paint, plastics, pharmaceuticals, detergents, etc. Thus, although there is no real danger of oil running out by 2020, increasingly expensive extraction and the many demands for this useful material mean that it may not continue to be available at a price and in a quantity that allow the economic operation of large numbers of passenger aircraft. This scenario explores the limitations and opportunities posed by a change in the level of fuel available for aviation. Alternative A: Mad Max

In this scenario, worldwide oil production peaks between now and 2020, as accessible and economically significant oil reserves dry up. Oil becomes increasingly expensive, requiring new techniques that deliver smaller quantities at a much greater price. (During 2004 the price of a barrel of light, sweet crude has typically been between $35 and $50; in the worst-case it could reach $180 or so by 2020, this being caused by a downturn in production rather than the end of oil supplies.)

Given that fuel for jet aircraft is not currently taxed, there is no possibility of cushioning increases in the costs. The military would have first call upon dwindling reserves. Civil aviation would suffer tremendously, with a drastic reduction in passenger numbers, and very high costs for the remainder. Ultimately, well beyond 2020, civil aviation might re-emerge using dirigibles. (Some studies have also involved nuclear-powered aircraft.)

Alternative B: Abundant Fuel

This scenario proposes a future world in which fuel is plentiful and hence inexpensive. It might result from a technological advance that allows aircraft to use some renewable source of energy. However, given the development time required for a radically different engine for civil aviation, a change to a hydrogen-burning engine, pulse detonation engine, or equivalent by 2020 is most unlikely.

Alternatively, one of the alternative large uses for oil, such as private motoring, might be eliminated by technical innovation or policy changes. Fuel stocks might be secured into the future by choosing to explore for oil in areas that are currently protected from environmental harm, such as Alaska or Antarctica. Technological developments that would delay the downturn in oil production (getting oil from wells previously declared exhausted, or making extraction in harsh environments possible) are also theoretically possible.

With cheap fuel, faster aircraft such as a new supersonic transport become possible, and may form a basis for competition. An increasing share of the world’s freight could be moved by air, since ‘lean thinking’ demands that stocks of goods should be offloaded as soon as possible. Even without a fuel supply constraint, the damage caused by greenhouse gasses might lead to taxes being levied upon aviation, and aviation fuel in particular. Thus, it is unlikely that fuel would become cheaper in real terms.




This pair of alternatives is associated with the following:

• Scenario 2: Aircraft Age, since an increase in the cost of fuel may influence the economic case for replacing inefficient aircraft.

• Scenario 6: Journey Length, since scarcity of fuel may make far-flung holiday destinations less attractive economically.

• Scenario 11: Environmental Issues, since an abundant supply of fuel for aviation, and a corresponding increase in the number of flights, could lead to increased contrails, and consequent global warming.

• Scenario 14: Private Aviation, since these fliers must also compete for increasingly expensive fuel.

4.3.9. Spare Parts Provision The present-day business model for the major engine manufacturers involves heavily discounting new engines in order to win market share. With these engines in service, they will ultimately consume spares to a value in excess of the original discount. The break-even point can easily be six or eight years into the future, however, and the business model fails if spare parts can be obtained from third parties. Thus, this scenario explores the degree to which manufacturers are able to lock operators in to a long-term revenue stream. Alternative A: “Can’t Beat the Real Thing”

Primes exert a stranglehold over the spares market, perhaps using technology such as embedded microprocessors within parts, making it impossible to operate an engine unless every component within it is ‘licensed’. (The built-in electronics may offer embedded sensors, etc., adding value to the product.)

If accidents occur and it is later found that the aircraft involved had ‘clone’ parts fitted, the type approval process might become much more stringent, and more thoroughly enforced. OEMs are likely to see their level of business increase under this scenario; Supplemental Type Approval (STA) based businesses are likely to find their scale and scope of operations restricted.

Safety would probably improve, but costs would increase since OEMs must maintain a capability to manufacture a wide range of spares throughout the service life of an airframe or engine. The logistics of spares support for maintenance would be of increased importance under this scenario.

Alternative B: Attack of the Clones

As an alternative to strictly-enforced type approval for spares, improvements in process monitoring, and machining and fabrication process quality, might widen the field of possible players in spares manufacture. Patents expiring (on both products and processes) could make it technically possible to produce parts, while anti-trust legislation could open up the marketplace.




Many aerospace businesses responded to slow growth around the turn of the century, the terrorist attacks of September 2001 and the SARS virus by downsizing. They may well find that they have lost vital expertise from the shop floor and cannot rapidly scale up their operations to keep pace when demand increases, giving new competitors an opportunity to enter the market. This pair of alternatives is associated with the following:

• Scenario 2: Aircraft Age, since aircraft are more likely to consume an adequate amount of spares if they are in service for a long time before they are scrapped.

• Scenario 10: East and West, since growth in new regions may be accompanied by growth in support services within those regions, away from the countries that have traditionally controlled the spares market.

• Scenario 13: Operator vs. Manufacturer, since operator power may take the form of choosing where spares are sourced.

• Scenario 15: Attitudes to Risk, since outsourcing of components may increasingly become the norm for some OEMs, who may find that they have transferred some capabilities to a future competitor.

4.3.10. East and West In recent years the talking point among market analysts in almost every industry has been the meteoric growth in the Indian and Chinese economies. While much initial business concerned the supply of goods and services to Europe and North America, the increasing prosperity that has followed means that these newcomers to the global trading arena could also offer huge new markets – if the wealth generated reaches the majority of the population. Growth in air travel in the East may mean a shift in the ‘centre of gravity’ of aerospace manufacture, as governments increasingly demand deals that involve offsetting, while present-day support mechanisms may need to be supplemented by opening new outposts. Alternative A: New Economies and Markets

Meteoric growth in India and/or China causes these countries to become the most important markets for air travel products and services. Western companies acquire businesses in the region, or enter into partnerships. Many components (and later, aircraft) are produced locally, this existing trend being strengthened by offsetting. Aircraft specifications may shift slightly to accommodate the mission profiles imposed by different destinations.

Alternative B: NATO Countries lead expansion

Despite an increasing part of the world’s manufacturing being undertaken in the Far East, low wages remain the norm in these overpopulated countries, so air travel growth fails to keep




pace with GDP. Europe and North America remain the principal markets for leisure travel, with consequences for manufacturers and MRO businesses. This pair of alternatives is associated with the following:

• Scenario 3: Partnerships, since this may represent the means by which a western business wins a share in the developing markets.

• Scenario 12: Space Activity, since it is by no means guaranteed that future space activity will be conducted solely by Europe and the USA.

4.3.11. Environmental Issues It is now a widely-held opinion that air travel is harmful to the environment, as described in Section 3.4.13. This scenario explores the future business environment in terms of the constraints placed upon operators. Will the utility of air travel encourage us to tolerate the harm it does, or not?

Some excellent technical advances have been made, but in an industry where assets remain in operation for 25 years or more, it is by no means certain that legislators will allow operators the luxury of gradual change. Alternative A: Green Goals

This scenario represents increasing recognition that the Earth is being harmed by industrialisation and its consequences, with air travel being one of the worst offenders.

Obvious first steps include introducing a tax on fuel, driving up the cost of flying. Ultimately (not within the time period under consideration) aircraft might have to employ nuclear power, since even hydrogen-burning engines produce water as a by-product, which acts as a greenhouse gas when released into the stratosphere. Flying at lower levels is not practical, since the fuel consumption would be much higher.

Perhaps surprisingly, one present-day measure to reduce the environmental impact of air travel actually reduces safety. The steep angle at which aircraft climb away from the runway is designed to limit the noise footprint of the airport, but in the event of an engine failure the angle of flight could further imperil the occupants. Clearly, future environmental measures must take other factors into account.

Alternative B: Grey Future

On the whole, governments and people choose to ignore gradual deterioration in the weather, air quality, biodiversity etc. in the period modelled. Some governments may be an exception, but pollution crosses national boundaries in any case. Under such a scenario, air travel may well continue to grow – not least as holidaymakers need to travel further to reach destinations that offer reliable sunshine (and more reliable snow, for winter holidays). This is




good for economic growth and employment, but may only postpone the need for radical changes that could slow global warming. This pair of alternatives is associated with the following:

• Scenario 2: Aircraft Age, since under green legislation older, less efficient aircraft may be grounded for technical reasons not related to airworthiness.

• Scenario 8: Fuel Availability, since some green goals actually increase fuel consumption.

4.3.12. Space Activity

Many of the businesses that manufacture passenger aircraft have also played a part in the exploration of space. In commercial terms, the space missions now being conducted constitute a low level of activity, with relatively few manned missions and a lower level of technical innovation than was seen during the ‘space race’. Attitudes could change, however, so this scenario allows the impact of a change in the level of space activity to be considered.

Alternative A: Near-Earth Orbit Only

Space activity shrinks below its present-day level, perhaps ultimately leading to the abandonment of manned space flight. Small, robot probes may continue to be employed for various scientific purposes, and tried-and-tested launch vehicles deploy commercial satellites.

Engineers formerly engaged upon the design and construction of spacecraft systems become available to other sectors within the aerospace community.

Alternative B: Ambitious Frontiers

The industrialised world moves into space with growing confidence, anticipating the day when there may be a commercial rather than purely scientific payback for the investment (though this is well beyond the timeframe considered by the current project).

The number of launches increases, perhaps to a point where space vehicles come to represent a major area of activity for many of the major aerospace systems integrators. Demands for personnel, materials etc. rise accordingly. This pair of alternatives is associated with the following:

• Scenario 10: East and West, since development in India and China may lead to a new ‘space race’.

• Scenario 11: Environmental Issues, since growing concern over environmental damage may lead to constraints being placed upon the number of launches made.




• Scenario 15: Attitudes to Risk, since space contracts necessarily involve a sizeable gamble.

• Scenario 17: Product Variety, since technical spin-offs from space research may lead to new devices that are subsequently fitted in conventional aircraft.

4.3.13. Operator versus Manufacturer Power

The negotiations surrounding the acquisition of new aircraft (and engines) are a tremendously complex process, as Sabbagh [1995] explains, referring to the negotiations surrounding the supply of the first Boeing 777’s:

“A bid package like that between United [Airlines] and Boeing has several elements. It might have as its starting-point a price per plane – of the order of $120 million for each 777. But this price would not necessarily be paid in full. There might be credit terms, by which Boeing lent United some money to buy the planes so that the initial amount was less. There would be elements in the deal that might specify favourable low interest rates for that credit, and a schedule of payments that helped the airline. There would be a lot of discussion of warranties. How long would Pratt [and Whitney] guarantee the fan blades for? What promises would Boeing make about the durability of some of the materials they used, and when certain parts had to be replaced? There would also be a lot of hard bargaining about guarantees, by which Boeing assured the airline that the plane could fly on the routes that United wanted with the full number of passengers.”

Sabbagh [1995]

Both the operator and the airframe and engine manufacturers had a great deal to win or lose in these negotiations, and they were conducted with great care. United clearly had a lot of power (They actually had thirty-two other engine/aircraft combinations to evaluate, including offerings by Rolls-Royce, General Electric, McDonnell Douglas and Airbus.) United’s power can be seen in the performance guarantees they were able to obtain at a time when the aircraft only existed on paper; the final deal also included agreements on the pricing of spare parts, and the clauses assuring resale value of used aircraft.

Furthermore, the order placed by United was for a combination of firm orders and options, allowing them to increase the size of their 777 fleet if the market proved to be buoyant. Sabbagh [1995] states that the cost of an option might typically be 1/10th of the purchase price (To further complicate matters, manufacturers have been known to return the option price despite its not being taken up, in an effort to maintain good relations with the operator.)

The 1990 negotiations relating to the Boeing 777, then, appear to show an all-powerful operator. Perhaps, however, if these negotiations were taking place at a time when passenger demand was exceeding capacity, or when many of the world’s airliners were facing retirement, the power might have resided in the hands of the manufacturers. (Costa et al [2002] shows that there was a substantial and growing surplus of passenger aircraft at the time when the negotiations between Boeing and United Airlines took place.)




Although related to their degree of control, the offering that the manufacturing business chooses to promote (such as ‘time and maintenance’, or ‘total care’) is effectively a response, rather than an element in the initial business environment.

Alternative A: The All-Powerful Operator

In this scenario there is over-capacity, worldwide, in the manufacture of civil airframes and engines. This may be driven by the desire of governments to retain key manufacturing capabilities, with the high level of employment involved and their obvious application to defence. Operators may be able to demand much greater transparency from the manufacturer, driving down the cost of new products and spares alike. The power of the manufacturer may be further eroded by the entry of new competitors, perhaps making low-cost spares at first, but ultimately offering alternative engines.

Some activities now being undertaken might strengthen the position of one manufacturer and the expense of others; Boeing’s proposed ‘plug and play’ wing architecture on the 7E7 would mean that switching between engines made by any of the major manufacturers would become simple. This makes the 7E7 desirable to the operator since it further empowers them in engine sourcing negotiations; changing between one manufacturer and another would be relatively trivial, and could be done part-way through an aircraft’s service life, contracts permitting.




Alternative B: The All-Powerful Manufacturer

A scenario in which the prime contractors can afford more of a ‘take it or leave it’ approach might come about as a result of negotiations between competing engine manufacturers. It may be decided that the current practice of discounting a new engine by up to 70% – selling the system at a loss in order to win market share – is no longer desirable.

Alternatively, the collapse of one of the major manufacturers would serve to reduce choice and remove excess capacity. (A major lawsuit might tip a struggling manufacturer into bankruptcy.) Under these circumstances, it would become much more difficult for operators to play one manufacturer off against the others.


• Scenario 2: Aircraft Age, since an older fleet implies that the business of selecting replacements is more urgent.

• Scenario 19: Spare Parts Provision, since the presence of strong competition in the spares market would make the practice of discounting impractical.

4.3.14. Private Aviation

Not all aviation is conducted by large-scale commercial operators and the military. There are many small aircraft in private hands, and many more owned by large corporations or charter companies. While private aviation typically involves different aircraft types to those used by the major operators, the two forms of air travel are not entirely dissimilar; privately-owned aircraft share airspace with commercial traffic at times, and require access to services such as air traffic control and flight planning, plus provision of fuel, servicing and landing rights at some airports.

While many of these issues imply that private aviation must compete for resources with large-scale commercial aviation, it is also useful, in that it provides a route for future commercial pilots to receive basic training. The pair of scenarios that follows explores the impact of a change in the amount of private aviation taking place.

Alternative A: Swarming Skies

In this scenario, privately-owned aircraft become increasingly common. This might come about as a result of new technologies such as composite materials allowing aircraft to be manufactured in volume, while improved avionics make piloting a new generation of aircraft a simpler process. Buckley [2004] describes research now underway that could lead to aviation coming within the reach of the masses – a prospect that most present-day aviators react to with horror.




Alternatively, growth in private aviation may come about in response to the circumstances affecting large-scale commercial flying, as an increasing number of corporations and individuals find it useful to retain an aircraft for their use at their convenience. In the aftermath of the terrorist attacks of September 2001 the major carriers suffered as the public lost confidence in the safety and security of flying, but chartering of business jets actually increased. Although perhaps intended as a temporary measure, some of the business jet passengers became hooked on the elegance and convenience of the private aircraft.

Alternative B: Squeezed Out

Faced with limited capacity at airports and in their supporting services, private owners and small businesses may find themselves struggling to pay increasing costs. Events at Palomar Airport (Gaona, 2004) show how easily the redevelopment of an airport to meet a growing demand for modern terminal facilities, etc. can lead to small businesses and enthusiasts becoming alienated, and forced to move their base of operations to more remote locations.

Ultimately, legislators may also have a part to play in squeezing out the light aircraft operators, perhaps demanding conformance with standards currently only applied to much larger passenger aircraft. Similarly, growth in the insurance premiums demanded of enthusiasts with older aircraft may lead to their being relegated to museum displays or the scrap yard.


• Scenario 2: Aircraft Age, since new regulations may force some of the older, privately-owned aircraft from the skies.

• Scenario 4: Airport Availability, since many private aircraft are currently housed and serviced at regional airports.

• Scenario 7: Conflict, since the terrorist events of September 2001 were seen to increase the demand for charter aircraft.

• Scenario 8: Fuel Availability, since private pilot’s license holders cannot pass increased running costs on to a customer.

4.3.15. Attitudes to Risk

The development of an entirely new product such as an aircraft or engine involves a great deal of risk, including (but not necessarily limited to) the following:

• Technical risk – the system may not perform as well as was hoped

• Volume risk – the demand for the system may not be as great as was hoped

• Cost risk – the system may prove to be more expensive to make than was planned.




In this field, product complexity tends to increase as systems are developed that meet increasingly demanding performance criteria. This makes the development process more convoluted, requiring a broad range of expertise and a great many man-hours of work. Collaboration is one way of dealing with increased product complexity, though this can introduce communication and logistics issues. Faced with the cost of evolving a new generation of solutions, businesses may change their practices…

Alternative A: Risk-taking

A risk-taking posture might come about as a result of a desire to break the stalemate at a time when there is overcapacity in the business environment. Boeing assert that Airbus have “bet the farm” (i.e., taken a gamble that it could not afford to lose) on the development of the A380 [Gow 2004]. Boeing have chosen to put their resources into an incremental improvement to a present-day aircraft concept (the 7E7 ‘Dreamliner’ is mid-sized and mid-range, but promises lower operating costs); the more radical ‘Sonic Cruiser’ and the 747X ‘Superjumbo’ have been shelved. Conversely, Airbus have given themselves a distinct ‘unique selling proposition’ in the 555-seat A380, by definition a more risky path to choose, since no operator has experience with a passenger aircraft of that size.

A risk-taking approach may also come from the bottom, as small businesses are set up to exploit advances in materials, or perhaps new software tools that reduce development costs. In such cases product variety may increase, and prices may fall. While it is unlikely that a new business could set itself up as a rival to Airbus any time soon, the manufacture of light aircraft and perhaps business jets could be within the reach of an ambitious risk-taker. (The recently-won Ansari X-prize contest illustrates how a small company that is prepared to embrace risk can achieve great things, even in the expensive arena of aerospace engineering.

Alternative B: Risk-avoiding

In this scenario, decision-makers within the aerospace industry seek to avoid risk wherever possible, developing products collaboratively in order to share risk, and share the benefits. (“Better to be in a partnership and get a share of an order, than to compete alone and perhaps see the whole order go to a competitor,” is the logic behind this risk-averse approach.) Mergers may well follow, to the extent allowed by law.

The ultimate endpoint of this approach appears to be a single, global aircraft offering. In defence products in particular, the post-war era has seen a shift away from successful development by small businesses such as Blackburn (about 5,000 employees), towards increasingly large clusters. The British Aircraft Corporation (BAC) was formed in 1959, comprising the Bristol Aeroplane Company, English Electric, Vickers-Armstrong and Hunting. Subsequently, BAC itself was absorbed into British Aerospace (BAe), along with the Hawker Siddeley Group (which included Blackburn) and others. Even so, European collaboration entered into on projects such as the Panavia Tornado and more recently the Eurofighter. Furthermore, Britain’s next major military aircraft purchase appears likely to be the Joint Strike Fighter, A US-led project involving several EU nations.




Under risk-averse leadership, the pace of innovation will tend to be slower, with primes incorporating proven designs rather than new technologies.


• Scenario 13: Operator versus Manufacturer Power, since the manufacturer takes a risk when refusing to accede to customers’ demands.

• Scenario 18: Business Start-ups, since these represent risk-taking on the part of operators. (Furthermore, manufacturers that offer financing services, or leasing, take a risk when dealing with a start-up operator.)

4.3.16. Size of Payload

A major factor in determining the specification for an aircraft is its payload; “the part of a vehicle’s load which earns revenue; passengers and cargo” [Compact Oxford English Dictionary, 2004]. In air freight, as with postal services, the cost of transportation is based upon the weight of the goods. Passenger journeys, however, are sold using the more crude approximation of the seat. This poses a problem since, in the developed world, average height is increasing with each generation. Average weight has been seen to increase even more rapidly. This may have profound implications for the configuration, and even the design of aircraft in the future. Alternative A: ‘Wide bodies’

Growing levels of obesity force operators to respond by increasing the size of their seats, or by requiring some passengers to travel in a different class, etc. (Southwest Airlines introduced a policy of charging ‘persons of size’ for two seats if they felt they would not fit comfortably in one [Kay 2002]. In truth, of course, this is for the comfort of neighbouring passengers.) A solution from the 1950s offers itself as well; weigh the passenger along with their luggage, with surcharges for excess weight. The net result is likely to be fewer seats per aircraft, with each ticket costing correspondingly more.

Alternative B: ‘Narrow bodies’

Although it may initially seem unlikely that the average weight of a traveller and their possessions could fall, this might come about if the demographic of fliers changed in the future. More children, or more fliers from among races that tend to be smaller, could mean that the average passenger is smaller and lighter, with implications for the layout of aircraft and the cost of travel.


• Scenario 5: Quality of Service, since a high quality offering will probably involve giving passengers more room within the cabin, and may allow them to transport more luggage.




• Scenario 6: Journey Length, since this also influences the amount of aircraft space that must be devoted to passengers’ comfort.

4.3.17. Aircraft Variety

If considered as a single, global business, the aerospace industry has a reasonably small range of products on offer; certainly small enough that any operator wishing to acquire new aircraft can becomes familiar with all the airframes and engines on offer. This range of products may widen in the future, however. In airframes, a new generation of Antonov, Ilyushin or Tupolev aircraft could make Russian offerings highly competitive, or a new aircraft might ultimately become available from India or China.

At any given time, of course, there is also a considerable fleet of older aircraft in service, all of which must be supported with spares and services. Indeed, under the present-day business model where new engines (and to a lesser extent, airframes) are heavily discounted, the legacy support phase is where profit must be made. Thus, it is desirable that older aircraft continue to fly and consume spares, but too many varieties of aircraft would complicate the business of keeping them supplied with the necessary spares.

Alternative A: Less Product Variety

Manufacturers that formerly conducted R&D operate on a ‘build to print’ basis in the future, perhaps as a result of mergers. The level of choice in aircraft falls as a result, with benefits in terms of simpler logistics for those who support and maintain aircraft. The operators’ power at the negotiating table when purchasing new aircraft may suffer.

Alternative B: More Product Variety

New manufacturers enter the market, or perhaps some well-known businesses move up a tier in the supply network. This may be a response to the failure of existing manufacturers to ramp up volumes in response to healthy demand. (Businesses that closed facilities and cut jobs during lean years may find it difficult to rapidly reverse their retrenchment.)


• Scenario 2: Aircraft Age, since an older mean age implies that there will be a broader range of types in operation.

• Scenario 9: Spare Parts, since a wider range of replacement parts will be more difficult to maintain.

• Scenario 13: Operator versus Manufacturer Power, since more choice would strengthen the negotiating position of the purchaser of aircraft.




4.3.18. Business Start-ups

Despite the fiercely competitive nature of the air travel business, hardly a month goes by without news of a business start-up in the sector. Although aircraft are tremendously expensive items, there is a surplus of grounded machines that can be brought back into service at relatively little cost, while internet-based ticketing has reduced transaction costs to a fraction of their former levels, and also allows a degree of advertising. Furthermore, it is not normal for operators to own their aircraft; they are normally leased, so setting up a small airline does not require colossal backing.

Alternative A: Tough at the Bottom

Viewing the success of present-day ‘no frills’ operators, a mass of entrepreneurs, and many well-known brands and businesses launch their own airlines. Little more than a catch-phrase, a logo and some advertising is required. Some prosper; some don’t. Each time one of these small operators folds other businesses will be willing to acquire their aircraft, landing slots, etc. MRO businesses may well see an increase in the amount of aircraft getting repainted!

Alternative B: Land of the Giants

In this scenario business start-ups become less common, perhaps as a result of legislation or bad publicity following problems. It must be remembered that the smaller operators typically operate older aircraft, and their flight crews tend to have less experience. This contributes to an increased level of hazard – though air travel is still the safest for of transport. If a spate of accidents were to occur, the public might eschew budget airlines. Under these circumstances the volatility of the sector would reduce and flag carriers with their own budget airlines could consolidate back into just the ‘giant’ brand.


• Scenario 2: Aircraft Age, since small airlines tend to operate older aircraft.

• Scenario 4: Airport Availability, since new competitors may find themselves limited to remote, regional airports.

• Scenario 6: Journey Length, since small airlines may tend to concentrate on profitable, regional city pairs.

4.3.19. Freight Activity This pair of scenarios investigates the relative importance of air freight, as opposed to passenger travel. Most freight is carried in the holds of passenger aircraft, so the two are




closely related, but airfreight represents an alternative income stream for struggling operators, and a ‘second life’ for many ageing aircraft types. At the time of writing, Rolls-Royce (2004) predicts that growth in air freight will exceeded growth in passenger traffic by 1.6% per annum. Alternative A: The Future is Freight

In this scenario, freight becomes an increasingly lucrative area of the operators’ business. This may be due to patterns of taxation, a protracted price war on passenger travel, or perhaps an increase in the demand for air transport as globalised businesses find they need to reach markets quickly with products with a short life-cycle.

The shift in emphasis is recognised by airframe manufacturers, and more new-build freighter aircraft are seen, with features included specifically for the purpose of handling cargo. MRO businesses that convert passenger aircraft into freighters may also see an upsurge in business.

Alternative B: People, not Packages In this scenario, the amount of freight carried falls, as a proportion of total air traffic activity. This may be the result of a downturn in manufacturing, or perhaps just a sharp rise in the number of passenger journeys. The cost of moving air freight may also become less attractive if a new generation of high-occupancy passenger aircraft come into use. Aircraft that use multiple decks for passengers may not feature a corresponding increase in hold space, so the net result would be less tonnage of freight per passenger. Increased competition from high-speed rail networks or ships could also reduce the level of air freight activity. This pair of alternatives is associated with the following:

• Scenario 2: Aircraft Age, since it is the aircraft that are considered unsuitable for passenger operations that tend to be converted into freighters.

• Scenario 4: Airport Availability, since freighters require landing slots, parking and ground services, just like passenger aircraft.

• Scenario 8: Fuel Availability, since the viability of freight activities is dependent upon the cost of flying.

4.4. FROM SCENARIOS TO THEMES

A theme is a set of changes with a common thesis. It is unreasonable to assume that most factors in the business environment remain constant while a single one is altered; selecting a set of changes with a common theme allows the exploration of more plausible futures. This is where the interrelationship between scenarios, as identified in Sections 4.3.1 to 4.3.19 is incorporated into the modelling process. If, for example, a future business environment is being modelled in which growth in airport capacity is severely constrained, the modeller may




also wish to investigate issues such as the amount of private aviation taking place, and the level of air freight activity, etc.

A theme, then, is selected by the person using the business environment modelling methodology, and is expressed in terms of a shift in one or more dimensions, in each case away from the present day state of affairs and towards either ‘Scenario A’ or ‘Scenario B’. The magnitude of the shift towards the selected scenario can be expressed by plotting a position along the scale, with the future business environment being expressed as a position in a multi-dimensional space.

In the early stages of this work it was envisaged that the tool for the plotting process would take the form of a booklet, with each page describing a dimension together with its pair of scenarios, and offering a scale that could be marked to indicate the reader’s opinion as to the shape they anticipated for the future aerospace business environment. However, some people using the methodology might wish to explore a variety of different themes; not merely the one that they feel represents the most likely future business environment, but also those that present valuable opportunities, or significant threats. For this reason, the mapping methodology has been expanded into an interactive tool, as Section 4.5 describes.

4.5. A SOFTWARE TOOL TO SUPPORT INVESTIGATION OF ANTICIPATED FUTURE BUSINESS ENVIRONMENTS

Section 4.4 described how the future aerospace business environment might be described using a set of dimensions. It will have been seen, however, that the generation of a model of the future business environment is a potentially complex process.

The VIVACE Interactive Business Environment Simulator (‘VIBES’) is an experimental prototype that presents the full range of initial business scenarios identified during the research to date, in a user-friendly environment (Figure 4.3). VIBES employs the same approach of presenting a scale, defined by a pair of opposite scenarios, as that described in the Section 2.2. Within the software, the position on each scale can be converted into a numeric value, and that can then be stored and used for calculation. The purpose of this approach is to identify the initial business scenarios that merit further investigation in the opinion of industry stakeholders. In return, users are given a tool that promotes thought and discussion, through the presentation of rough-cut forecasts.




Figure 4.3: The VIBES software

In order to limit the apparent complexity of the business environment definition task, the user is invited to identify their role, i.e. their industry. Examples include operator, prime, legislator and MRO, as Figure 4.4 shows:




Figure 4.4: Selection of role, within the VIBES software

With their place in the value chain identified, the user can then choose to investigate scenarios that impact upon their business, although it is possible to investigate the full range of nineteen dimensions if desired. Figure 4.5 shows how the set of initial business environment scenarios is reduced to a subset that matches the role the user has selected. Each rectangle is a button, linked to a page where the corresponding dimension is explained in detail, and a slider is shown, allowing the user to select a position along the scale that represents future change towards one or other of the two scenarios (Figure 4.6).




Figure 4.5: Initial business scenarios available to the user, following their nomination of an

industry role




Figure 4.6: Software-based presentation of a pair of business environment scenarios

All sliders begin in a central position, representing the current state of affairs. The user is free to alter as few or as many as is desired, using the position of the slider to indicate anything from a small change up to a major swing towards one or other of the extremes described in the text. The position of each slider is encoded within the software as a numeric value. Thus, when the user is satisfied that they have identified the combination of changes that they wish to model, they have constructed a theme. By this method a complex future business environment can be stored as a simple collection of numbers. These have considerable value to the research staff on WP2.1.1, since they may indicate aspects of the future aerospace business environment that are of interest, and should be considered as targets for further investigation.

For the user, the incentive for working through this process lies in the rough-cut forecasts that VIBES produces. Based upon the changes that the user has defined, VIBES attempts to determine the net change in a number of key industry metrics. Each of the nineteen dimensions has a weighting against each metric, indicating the magnitude and direction of impact. For example, a reduction in fuel availability would have a strong tendency to increase the cost of a typical ticket.

Each of these relationships is defined in a matrix that the typical VIBES user will never see. For WP2.1.1 staff, however, it will allow the settings of the software to be adjusted and validated without recourse to programming. Figure 4.7 shows an example of the pop-up window where the relationships between dimensions and key industry metrics are defined.




Figure 4.7: Defining the relationship between a pair of scenarios and selected industry

metrics, using VIBES’ developer mode.

As far as the user is concerned, the output from the software is a set of rough-cut forecast data, showing the net changes to the industry, based upon the scenarios they have selected. VIBES does not attempt to predict numerical values for any of the business metrics – this would require a much more complex underlying model – but can show likely trends in each metric.

The full list of industry metrics has yet to be defined. At the time of writing, the following had been implemented (units shown in brackets):

• Passenger journeys (total per year)

• Mean passenger journey length (km)

• Seat occupancy (%)

• Typical ticket prices (currency)

• Freight carried by air (total tonnage per year)

• Mean freight journey length (km)

• Safety problems (incidents per year)




• Security problems (incidents per year)

• Airport maximum capacity (million passengers per year)

• Mean passenger aircraft age (years)

• Mean new build engine list price (currency)

• Mean new build airframe list price (currency)

• Navigation charges (currency)

• Landing charges (currency)

• Value of used aircraft (currency)

• Value of aircraft options (currency)

It is useful to see the net change in each of these metrics plotted, since the scenarios selected may reinforce one other, making a bigger change, or one may counteract another. For example, an increase in operator partnerships might tend to drive the price of a ticket downwards, while increasingly scarce fuel has the reverse effect. Only when all the changes that form a part of the theme have been mapped can conclusions be drawn. Figure 4.8 shows a typical VIBES output:

Figure 4.8: Sample screen from the output phase of the VIBES software

It is hoped that the rough-cut forecast function provides sufficient incentive to encourage industry experts to experiment with the VIBES prototype. In addition to providing information




for the user, VIBES can also store information on the themes that have been explored by users, and could thus become a significant data collection mechanism for Task 2.1.1. Future work within the task will involve the construction of detailed models using system dynamics, as Chapter 5 explains, so the software described in this section could prove extremely useful in identifying the specific areas that should become the focus of attention. VIBES will continue to be developed in early 2005, with a prototype plus interim outputs and validation being a M18 deliverable.

4.6. INVITATION FOR FEEDBACK ON BUSINESS SCENARIOS As with the validation process now underway with the factors map presented in Chapter 3, the initial business scenarios described in Section 4.3 need to be assessed and validated through interactions with industry stakeholders. This might best be conducted by circulating the software tool, rather than a paper document, since one of the main goals at this stage is to understand which themes are felt to be of the greatest importance, and this may be deduced by examining the themes that users construct. Initial feedback on the technical approach taken has been positive, indicating a willingness to experiment with the system. (Of course, if it is found that a commonly-desired theme cannot be constructed using the nineteen dimensions provided to date, it may be necessary to alter or add to the current set of scenario pairs in a future version.) Regardless of whether it is felt that a particular theme should be investigated because it represents the most likely future business environment, or that it presents the greatest opportunities or poses the most severe threat, it is vital that steering is obtained from businesses that provide or support air transportation, since this can then drive the formation of models that focus upon areas of concern.

4.7. CONCLUSIONS This chapter has described a methodology for describing the future aerospace business environment using scenario analysis. Building upon the factors mapping activity described in Chapter 3, nineteen pairs of scenarios have been proposed, each pair describing one dimension upon which the future business environment can be plotted. A modelling methodology was established whereby a position is indicated on a scale for each dimension, between the extremes described by mutually exclusive scenarios. This was then converted into a software tool, using weightings to produce rough-cut trend forecasts as a result of users’ choices. It is hoped to make the software tool available to the VIVACE community early in 2005 as part of a data collection exercise.




5. CHAPTER 5: BUSINESS ENVIRONMENT MODELLING

5.1. INTRODUCTION

Having identified the key issues from developing initial business scenarios, more detailed analysis using a modelling tool will be conducted. The aim of the modelling process is to understand the dynamic behaviour of the business environment, to understand how different policies and variables may impact on future aerospace scenarios. Here we outline the rationale for modelling, previously successful studies and we propose an approach based on systems dynamics.

5.1.1. Scope and aims of modelling

The research described in early chapters is centred on defining the characteristics of the external business environment such as trends in market demand and their drivers. Our approach has primarily been to isolate ‘external factors’ from ‘internal factors’ in order to develop business scenarios. However, key players such as operators, governments and manufacturers all play a part in shaping market behaviour. This area of the research considers the impact of the strategies of key players on the business environment. Business environment modelling may be used to examine possible responses to future business scenarios so that the consequences of future strategies can be examined both in terms of intended and unintended responses.

Policies are used to describe the ways that key players can influence events and activities. A policy may be a business strategy or a governmental regulation. The focus of our research within WP2.1.1 is the development of value chain strategies for aero engines for the future manufacturing and service provision. Therefore, the focus of the modelling work will be on evaluating business strategy in the context of value chain management. Modelling of aircraft and passenger demand is likely to be required in order to understand the behaviour of engine demand. It is unlikely that a value chain strategy can be considered in isolation because it is inextricably linked to business strategy and government policies.

In summary, the modelling of the business environment is driven by the need to:

• Understand the dynamic behaviour of the market i.e. how customer demand changes over time.

• Identify the impact of policies on market behaviour including government policies, business strategies and value chain strategies.

5.1.2. Application of the model




Considerable expert knowledge in market analysis resides with the aerospace commercial planners. Although passenger and operator demand information is widely available from market research enterprises there is significant complexity and difficulty in predicting the impact of demand profiles. (See Chapter 2 for a more in depth analysis of demand prediction processes.) In few industries do politics, regulation and social trends have a greater impact. Mechanisms are needed for corporate planners to understand the behaviour of this multitude of factors and to interpret them into implications and possible response strategies.

Another aspect that adds complexity to the job of the commercial planner is that the aerospace industry has relatively slow ‘clock speed’ – manufacturing lead times are long which means that the time from changes in passenger demand and changes in capacity can be several years. These lags in supply and demand mean that there are delays between their actions and the impact being felt by the industry. This makes it difficult to assess the impact of decisions. The business environment modelling should provide a decision support model for commercial planners to add insight into market behaviour. The model should allow a commercial planner to pose ‘what if?’ questions such as ‘what if operators are able to detect changes in demand more quickly, what effect will this have on our order book?’

5.1.3. Approach to modelling

Figure 5.1 illustrates how the business environment modelling work complements and builds on the other work within the VIVACE work package 2.1.1. The published trends that were described in Chapter 3 have initiated the development of the interactive tool VIBES to capture expert opinion on trends and responses. This requires significant further development but its potential has been demonstrated. The factors mapping that describe the relationships between market characteristics has been used to define key factors for use in the model. The business environment work should also use the philosophy of providing visualisation of these complex issues to allow users to learn and have insights in this complex area.

Modelling Factors mapping

Published trends

Trends identified by VIBES

Key relationships

Descriptive

Numeric outputs

Representation of key elements

Dynamic behaviour

Figure 5.1: Business environment modelling complements the other descriptive approaches




Figure 5.2 illustrates the flow of information between the activities to describe the aerospace business environment and specifically the analysis of relationships between factors. The factors mapping process has provided information to form the basis for constructing the logic behind the VIBES software. Business Environment Modelling should provide further information about the relationships. Modelling dynamic behaviour will provide information about the factors that dominate in creating market dynamics. The development of response scenarios will be supplemented by the modelling of cyclical demands and experimentation with methods for managing demand.

Figure 5.2: Flow of information between the WP2.1.1 activities

5.2. STATE OF THE ART MODELLING METHODS FOR EVALUATING MARKET BEHAVIOUR AND STRATEGIC RESPONSES

A review has been made of the state of the art modelling methods relevant for the aerospace context. It is important that existing knowledge is drawn on for modelling the complex and dynamic market behaviour of the aerospace industry.

5.2.1. Methods for strategy evaluation

Factors

Mapping

VIBES

Interactive software –

gathering expert opinion

Business

Environment

Modelling

Final ScenarioDescriptions - business scenarios - response

Selection of

key scenarios

Validation of

the strengths of

Relationships

Matrix of

relationshipGenerate

response

scenario

Capture of

dominant

relationship

Cyclical

demand and

analysis of Metrics




The nature of demand is highly cyclical in the aerospace industry. There is a need to understand strategies for effective management of cycles. What strategy tools are available that may be able to provide a framework for this investigation? Our review of strategy tools has revealed that there are many diagnosis tools to describe market drivers such as force field diagramming, impact analysis and the five forces (see for example, Garrett, (2003)). However, these tools do not allow for easy evaluation of the performance of strategies. Additional calculations and reports need to be prepared for each strategy or ‘what if’ question that is under investigation. For instance, there is no automatic response of the model on the impact on demand.

5.2.2. Methods for evaluating market behaviour

A similar situation was found for the methods used to evaluate market behaviour. Sophisticated demand prediction methods have been developed by aerospace experts. However they do not necessarily allow for consideration of the impact on strategy.

An example of one of the methods for predicting demand is provided by the regression model of Lyneis (1998). The development of this model provided evidence that the best fit for aerospace demand was based on the following formula:

Sales = f [ GDP growth lagged one year; oil price change lagged one year].

The correlation coefficient was not high from the regression analysis (R = 0.4) which suggests there is not a high level of confidence in this method of calculating demand. Significantly, this regression analysis failed to predict peaks and troughs. Inaccuracies in predictions like this cannot be easily ignored by a market that requires high long-term investments.

5.2.3. Simulation methods for evaluating market behaviour and strategic responses

Simulation should provide a method of modelling both market behaviour and strategic responses in an integrated model. It offers useful mechanisms in this context because it provides us with a model for experimenting with different variables. A business environment simulation model will calculate the implications of all the relationships that have been specified for the variables in the model.

The focus of this research is to model dynamic market behaviour. Continuous simulation is likely to be a powerful tool for modelling dynamic behaviour. System Dynamics is a widely used method of providing user-friendly continuous simulation.

5.2.4. Using System Dynamics to Simulate Demand and Evaluate Policies




System dynamics was originally developed in the 1970’s by Jay Forrester but has seen a rise in popularity over the last few years (Sterman, 2000). It has been adopted as a tool by commercial planners in other sectors - the automotive sector, the health care service industry – as well as the aerospace industry. Companies such as Lufthansa Airlines, General Motors and the National Health Service (UK) are currently using the modelling techniques in corporate planning and inventory management. Other industries have used it as a tool for justifying buffers and the absorption of contingency costs for cyclical demand. System dynamics has seen a recent surge of use in new areas and particularly in the modelling of differences between capacity and supply for generic value chains (e.g. Spengler & Schroeter, 2003).

System dynamics modelling has the potential to yield valuable insights into value chain strategy and the behaviour of future business environments in the aerospace industry. One of the key benefits of adopting system dynamics is that it may allow the evaluation of performance improvements from strategic changes. Typically both market demand behaviour and its implications are contained in the same model.

System dynamics is based on the fundamental principle that dynamic systems have feedback. The feedback may be intended or unintended and may be positive and reinforcing or negative and balancing. It is particularly useful in policy design where there are many interwoven relationships and feedback loops between policies. System dynamics methods and techniques have been applied by consultancies and academia to a wide variety of industries. Methods for developing these types of models are well established (Sterman, 2000) and techniques are available for extensive sensitivity testing which is important for a volatile market such as aerospace demand. System dynamics provides a toolkit of techniques to allow representations of complex systems for visualising and understanding the behaviour of multitude of variables. These include sub-system diagrams, cause and effect diagrams and ‘stock and flow’ diagrams. The core model is based on levels of ‘stock‘ and ‘flows’ between stocks which are represented as rates of increase or decrease of variables. It is the core elements that provide the calculations for the model. The terms derive from the roots of System Dynamics in inventory management modelling.




Figure 5.3: A basic system dynamics model based on Liehr (2001).

Figure 5.3 shows a basic system dynamics model in an aero-industry context. Orders arrive with the manufacturer at a specified rate. This influences the manufacturing rate which is drawn as a ‘stock’. On delivery of aircraft the capacity of an aircraft fleet reaches a new level of stock (capacity stock). This will decrease at a rate dictated by the retirement of aircraft. A feedback loop is drawn between capacity and orders to reflect the usage of the fleet. Other causal factors influencing the system elements are illustrated with arrows.

System Dynamics differs from discrete event simulation which is now widely used in factories for inventory management (VIVACE WP2.5 and VIVACE WP2.1.4). System Dynamics is based on ‘continuous’ simulation techniques. This type of model is more appropriate for variables that change continuously over time rather than in increments. For business markets, the system variables change continuously and there are many variables that cannot be controlled but must be responded to. The purpose of system dynamics modelling is to represent a complex system by its dynamic factors that are easily understandable. This allows the user to experiment and to find the factors that can be modified in order to control the system to the required performance criteria. These factors act as levers to the system and are often called the ‘leverage points’ of the model.

System dynamics can allow diagnosis and understanding of the underlying causes of industry dynamics. This means that system dynamics can also provide mechanisms for monitoring changes thus providing early warning systems to allow users to learn (Lyneis, 1998).




5.2.5. Demonstrations of Aerospace System Dynamics Models

Two models are highlighted here should the reader wish to further explore the functionality of system dynamics. The models have been selected because they are based on modelling aerospace market behaviour and because user interfaces are provided to step the user through the core elements of the model. It should be noted that they are for illustration purposes only and are therefore simplistic models. The following models are readily assessable via the web addresses given:

• Changing air traffic control policies at Heathrow airport to reduce delays -the model ‘Airport Runway Capacity’ can be downloaded for running on a local computer from: [http://www.cognitus.co.uk/ithink-requirements.html]

• Cycles in demand and supply of aircraft - the model ‘Airline Commodity Cycles’ can be downloaded for running on a local computer from: [http://www.cognitus.co.uk/ithink-requirements.html]

5.2.6. Using Simulation Tools and the Practicalities of Integrating Data

There are three simulation software packages that are commonly used for system dynamics modelling:

1) iTHINK from ISEE Systems [http://www.iseesystems.com]

2) Vensim from Ventana Systems [http://www.vensim.com]

3) PowerSim from PowerSim Software [http://www.powersim.com].

Demonstration editions of the three software packages have been evaluated. The three packages share very similar features for model construction.

Vensim is likely to be selected for future modelling of the aerospace business environment.

There are three reasons for this:

1) The user interface allows a user to vary key parameters and to visualise the results of experiments to control the system through a ‘control dashboard’.

2) Vensim has been used by other modelling applications in the aerospace industry for consultancy purposes but is also widely used in the academic community because of it computational sophistication (e.g. Liehr et al (2001) and Salge & Milling, (2004)).

3) A free version of the Vensim modelling software is readily available on the internet - Vensim PLE – that allows viewing and experimentation with models. This will allow




the VIVACE business environment model to be more widely available to VIVACE participants.

An important aim within the VIVACE project is to provide integration of the tools developed. The use of software such as Vensim allows data to be input from a spreadsheet to provide efficient data handling from many sources. This effectively allows the model to be controlled from other programs if required.

5.3. EXISTING MODELS OF THE AEROSPACE ENVIRONMENT

Three key system dynamics models have been identified that have been used to analyse the aerospace market and to develop policies. The approach, system elements, techniques and findings are described for each of these models.

5.3.1. Model for investigating aircraft ordering policies by Lufthansa

Approach - The development of this model was commissioned by the Corporate Planning Department of Lufthansa Airlines in Germany (Liehr et al, 2001). The goal of the project was to use system dynamics and statistical forecasting models to understand how they, as an airline operator, could improve their effectiveness at managing business cycles. The approach was not to provide precise numerical replication of market behaviour for demand prediction. The project aimed to find influences on the behaviour of the market e.g. ways of increasing the stability of the market to reduce swings in demand for the business. In particular, the model was used to find leverage points to influence the aircraft buying market through fleet and capacity management. The pressure on rapid capacity growth to prevent losses in market share leads to excess capacity in passenger flights. Lufthansa wanted to find ways of ordering ‘counter-cyclical’. This would mean ordering when demand was not at a peak but could give lower purchase prices and shorter delivery times for aircraft. The model allowed Lufthansa to test their influence on the market as a buyer of aircraft. System elements – The model is based on a core model which has the sub-elements of (1) demand, (2) capacity, (3) surplus or shortage of seats and (4) rate of supply of aircraft to address this surplus or shortage. The conceptual models were developed through group sessions and interviews with Lufthansa staff. The modules that supplement this core model are:

1) The airline marketplace – other airlines and manufacturers of aircraft 2) The airline (Lufthansa) – a micro model of the company’s policies 3) The airline competition – an ‘airline selector’ for passengers.

The factors influencing ordering policies for aircraft that were modelled included: 1) No commitment is made to new aircraft until profits from existing commitments have

been assessed by the airline (mid-term evaluation of operating costs).




2) Passenger growth forecast. 3) Number of daily take offs per aircraft (legs).

The model exhibited cyclical behaviour due to ordering policies. The characteristics of these cycles can be summarised as follows:

1) Oscillations in demand are due to the delay in recognising shortages in capacity and the order-delivery delay for aircraft while the craft is manufactured.

2) A typical cycle referred to as the ‘kusnet’ cycle which means that once the surplus capacity has peaked there is a delay while the depreciation of existing aircraft runs out. After this period of depreciation order rates can increase.

3) Period of the cycle is eight to ten years (this is typical for machine investment or economic cycles – referred to as ‘Juglar’ waves).

Techniques - A statistical forecasting model was developed to provide the start point for predicting the fluctuations in operating profits and delivery of aircraft. The statistical calculations were based on multiple regression analysis. The next stage of development used the data generated from this analysis within a system dynamics model. This system dynamics model was designed to provide a decision support tool to test alternative strategies. The time horizon modelled was 1970 to 2010. This represented a forward time horizon of nine years into the future. Findings – Lufthansa were seeking to find policies that would stabilise the cyclical nature of aircraft demand. A somewhat surprising result of the modelling project was that the cycles were found to be generated within the airline industry rather than by ‘external’ factors. This is surprising because the accepted wisdom in the aerospace industry is that world GDP influences demand. GDP may be responsible for the amplitude of demand but not for the dynamic cyclical nature of the market. The cyclical nature is generated by ordering policies for aircraft. The intended or unintended capability for the industry to create internal cycles has been noted in other industrial sectors for industrial products. The leverage points of the system for the airline operator were demonstrated to be: 1) Improved capacity management – counter cyclical planning 2) Network planning – shifting capacity from one region to another 3) Flexibility in aircraft management – retirement and leasing.




5.3.2. Model for predicting demand for a commercial jet manufacturer

Approach – the modelling work was undertaken between 1987 and 1994 by the Pugh-Roberts Consultancy for an unnamed commercial jet manufacturer and later for a supplier to this manufacturer (Lyneis, 1998). The project set out to provide a model of the demand for jets. This model was to be calibrated with available demand data for prediction of future demand. The users of the model wished to understand how they could provide better capacity management through understanding their customers’ ordering. Improvements in capacity management were identified in two phases:

A) How can excess capacity of jets be avoided? The industry has a tendency to over- expand. Historical trends show that orders for jets are greatly amplified.

B) How can downturns in business be ‘bridged’ when order book levels take a downturn? The modelling project reviewed the causes of downturns in aircraft ordering due to market behaviour further down the value chain.

Policies for manipulating manufacturing slots by the aircraft customers were acknowledged. The modelling work sought to reduce this manipulation.

System elements – the model is based on four ‘loops’. The three reinforcing loops represented the manufacturing lead time based on manufacturing capacity, the pricing of tickets based on demand and the effect of passenger experience on ticket demand. A balancing loop represented the revenue stream from passengers and aircraft orders.

Two additional modules were added to investigate the impact of the used aircraft market. The first model reflected the relationship between newly ordered aircraft and a depression in prices on the basis that used aircraft are sold to other airline operators who buy these in preference to new aircraft. The second module modelled the impact of financial dynamics and cash flow availability on the investments and decline in the industry.

Techniques – passenger demand is modelled as a dynamic variable in the model. In contrast the capacity of aircraft manufacturers is an external variable to allow ‘what if …?’ questions to be investigated using the model. The period modelled was ten years (1976 to 1986) with measurements calculated at one year intervals. Demand was disaggregated into a matrix of international / domestic and global regions.

Findings – the demand predictions from the simulated model matched the historical data much more closely than calculations made using regression methods. The impact of different bridging strategies on profit was evaluated. An overview of the successful bridging strategies is as follows:

• If demand is slow:

– No bridging

– Carry inventory

• If demand is moderate:

– Use a ‘half bridge’ – gradually lay off half of the additional workforce




– Or use a ‘full bridge’ – build semi-finished inventory.

In addition the model successfully predicted the growth of market share of companies previously responsible for financing, into companies leasing aircraft.

5.3.3. Evaluating the airline operator strategies – Southwest Airlines v People Express Airlines

Approach – this research work sought to explain the causes of failure and success of the business strategies adopted by airline operators (Salge & Milling, 2004). The performance of two companies – Southwest Airlines and People Express Airlines – was used for the base data. These two airlines provided contrasting approaches to business strategy; Southwest Airlines, the ‘success story’ adopted a route strategy of flying point to point whereas People Express had a hub and spoke flight strategy before it suffered a catastrophic financial failure in the 1980’s. The modelling work focuses on the rate of growth of these two companies and how the growth was achieved (People Express used a high usage of aircraft giving higher capacity and high levels of collaboration with airline partners). See table 5.1 for a summary of the main differences between the strategies of the airlines. It also provides new insights into the constraints of airlines in adopting the two strategies. Flying to primary airports as People Express Airlines were required to do because of their strategy of hub and spoke routes meant higher levels of congestion.

Table 5.1: Summary of the strategies of the two case studies

Case study A –

People Express Airlines

Case study B –

Southwest Airlines

Route

Hub and spoke

Point to point

Airports

Primary airports

Non-congested airports

Lower turnaround times or aircraft

Aircraft

High workload

Many different types of aircraft

Moderate workload

B737 only

Partnerships Many alliances

Less alliance

Growth rate High accumulation of assets

Lower accumulation of assets

System elements – the model comprised of sub-systems that relate to assets and their rate of accumulation. The four elements were defined based on whether the assets were related to the firm or to the industry and whether the assets were strategic decisions on assets or the ownership of assets. In summary the four sub-systems were: strategic industry factors,




assets available on the factors market, strategic assets of the firm, and assets available to the firm. The assets that are modelled were financial resources, number of aircraft, staff, airports and passengers. Less tangible assets such as staff morale and the reputation of the airline were also represented in the model.

Techniques – the model was simulated using Vensim system dynamics software. The performance of the strategies of the two case studies was examined. The model is also used to examine two ‘what if’ scenarios that were based on combinations of the strategies of the two companies:

1) What if People Express Airlines had accumulated assets at a lower rate of growth? What would their performance have been?

2) What if Southwest Airlines had accumulated assets at a faster rate of growth? What would their performance have been?

Findings – The evaluation of these two cases give insights into the performance of low cost airlines and ‘full service’ carriers. The early results from the model suggest that the growth rate of low cost airlines is essential for the financial success of the lost cost, ‘no-frills’ operator strategy. Additional work is required to fully validate the results of the model and to confirm the results of initial policy experiments. The results published to-date are based on investigations of the success of combining policies from the business strategy of People Express Airlines with policies from the business strategy of Southwest Airlines. Simulation results indicate that the strategy adopted by Southwest Airlines gives a better financial performance than any other combinations of policies i.e. flying to a loosely coupled point-to-point network of secondary airports and owning a fleet of the same type of aircraft.

5.3.4. Conclusions on existing models

The Lufthansa model focussed on the demand for passenger travel and does not incorporate freight demand. The impact on the cumulative effect of freight on passenger travel should be modelled to fully appreciate the dynamics in the market.

All of the models reviewed incorporate airline operator elements. This recognises the role of the operator in the value chain. The speed of response to changes in passenger demand was found to be important in two of the models. Monitoring demand changes are therefore an essential competency for airline operators. It is therefore important that mechanisms for monitoring changes in demand are understood. This would offer the basis for evaluating a wide range of policies and evaluation of possible future scenarios.

5.3.5. Potential approaches in System Dynamics for Modelling of the Aerospace Market




This section outlines promising directions for system dynamics in VIVACE 2.1.1. The VIVACE system dynamics models could build on existing models by including:

1) Freight demand

2) Service aspects

3) Engine manufacture.

The modelling of the business environment should give insight into the impact of manufacturing cycles and how they can be managed more effectively.

One fundamental area to explore is the policies that can be used to respond more effectively to changes in demand in the market. How can a manufacturer detect changes in the market dynamics and respond accordingly?

All of the reviewed models are constrained to manufacturing aspects and do not consider the support of service elements of the product offering. Service is a key aspect of the WP2.1. It is therefore proposed that service elements are incorporated in the VIVACE model. One of the key questions of manufacturers of aerospace equipment is how service can be provided to counteract the cyclical nature of demand.

5.4. PROPOSED MODELLING

Firstly the scoping of the proposed model is described. This is a key stage of the modelling work which includes problem definition and the description of the dynamic behaviour.

5.4.1. Problem definition

Many areas of concern have been raised in the development of future scenarios (in Chapter 4):

• What will the changes in operating policies of airlines be?

• How will aircraft be reallocated?

• What will the trends in services be?

• What will the response by operators and leasing companies to new service provisions by aero manufacturers?

• What will passenger attitudes to travel be?

• How will service supply provide sustained profitability for the EU aerospace engine value chain?




5.4.2. System diagram

The underlying philosophy of the VIVACE project is to integrate the extended value chain. Other industries have found that sub-optimal decisions are taken by managers because they consider only their local segment of the value chain. This can lead to cyclical behaviour and a phenomenon known as the ‘bullwhip effect’ where responses are amplified up the supply chain. These sub-systems have been selected because they represent the key decision makers in the extended value chain. The sub-system diagram shown in Figure 5.4 illustrates the architecture of the model. Three variables influencing the system are shown: population, fuel price and GDP. The system is de-composed into five main sub-systems: passengers, freight, operators, system integrators and engine manufacturers. Each of the sub-systems has feedback loops to other sub-systems. Each sub-system has a decision-making element which is shown within the sub-system. The decision-making element is characterised by delays because there is usually a lag between a change in environmental conditions, detection of the change and action to respond to the change. See table 5.2 for our analysis of the delays within the five main sub-systems.

5.4.3. Definition of modelling variables

It is important to define two types of variables in the model – those representing decision variables (that can be controlled) and those that represent inputs to the system. The external factors are referred to in system dynamics terminology as exogenous variables. The internal factors likewise are referred to as endogenous. Table 5.3 lists the variables to be incorporated into the model and separates them into exogenous and endogenous.

5.5. MODEL DEVELOPMENT AND USE

Having defined the scope of the model, the following section describes how such a model might be built and tested. The modelling of factors will be constructed from the descriptions of relationships provided by factors maps.

5.5.1. Modular build of the model

The model could consist of three modules. Since it would be a large model it will be constructed in three phases. The base model will be constructed in phase 1. This will simulate the decisions of the manufacturer in moderating cyclical demand variations. The second phase will incorporate value chain and asset requirements to respond to demand variations. The final phase could incorporate the airline decision making on passenger demand variations.




5.5.2. Phases of testing and validation of the model

The phases of testing and validation are based on the framework set out by Coyle & Exelby (2000) who have compiled good practices for rigorous development of systems dynamic models.

The phases of the testing and validation of the model will be:

1) Confirmation of the mental model – confirmation that system elements represent the real world.

2) Verification of the simulation model – confirmation of the dynamics theory behind the model and technical accuracy.

3) Validation of the simulation model - A base case of engine manufacture to compare the model against historical data will be used.

The first phase would require the most intensive effort, needing input from key experts to validate the representation of the key elements.

5.5.3. Policies design

A policy matrix could be developed that will describe the new strategies, structures and decision rules to be tested by the model. These policies could be informed by the results from the VIBES software. Additional edits to the models could be established then. The model could evaluate the combination of policies.




Table 5.2: Delays in the aerospace industry

Decision-making

Decision maker

Dynamic variables

Detection of changes

Action Time

Experience Passenger Customer exposure to new services and operators.

Demand for new types of services.

Change flight schedule.

Time depends on the detection and decision making effectiveness of the operator.

Logistics policies

Freight Customer exposure to new services and operators.

Demand for new types of services.

Change flight schedule.


Buying policies

Operator Performance of aircraft.

Changes in operating.

Choose aircraft supplier and place order for aircraft (or stop order for aircraft).

Time depends on investment cycle and technology changes.

Detection of demand changes

Operator Demand for services from customer.

Bookings of types of flights e.g. growth in low cost point to point.

Order new aircraft.

Retire aircraft.


Capacity judgement

Operator Flights offered and demand.

Aircraft utilization and seat load.

Order new aircraft.

Retire aircraft.


Detection of demand changes

Systems integrator

Demand for service from airline (changes over time as customer is exposed to new services)

Alignment of service offerings with customer needs

Develop new services.

Add new assets.

Time depends on the detection and decision making effectiveness of the manufacturer.

Capacity judgement

Systems integrator

Passenger and freight growth trends. Capacity

Industrial data on trends. Customer slot reservation and cancellation.

Aircraft delivery. Recruitment of staff.

Manufacturing lead time (24 months).

Training time.

Redundancy periods.

Asset accumulation

Engine manufacturer

Demand for engines. Value chain capacity available.

Industrial data on trends.

Order book.

Add assets to value chain.

Manufacturing resource purchasing and installation.

Training time.

Service support

Engine manufacturer

Demand for service from airline

Alignment of service offerings with customer needs

Develop new services.

Time depends on the detection and decision making effectiveness of the manufacturer.

Table 5.3: Definition of variables




Exogenous Endogenous

Population Airframe manufacturing lead time

GDP Engine service support capacity

Fuel prices Engine maintenance support capacity

Engine manufacturing capacity

Table 5.4: Build phases of the model

Phase Module

Phase 1

Detecting changes in demand by the manufacturer

Phase 2 Detecting changes in value chain requirements

Phase 3 Detecting changes in demand by airlines

Figure 5.4: Sub-systems model

5.6. CONCLUSIONS




This chapter has reported some proposals for modelling of the future business environment. Business modelling should provide insights into the behaviour of demand and buying policies of the key players in the aerospace industry. This chapter has provided an overview of the kind of model that could be constructed and applied to this problem.

5.6.1. Status on business environment modelling

The approach recommended for business environment modelling is system dynamics. This can be used as the basis for constructing and simulating the behaviour of the aerospace market and policies for responding to demand dynamics. An initial model has been proposed which uses insights on market behaviour from earlier system dynamics models. This modelling work can complement the other initiatives in future scenarios descriptions and can provide the basis for the development of response scenarios.

5.6.2. Next steps in modelling

It is essential that any model combines the perspectives of key experts (such as commercial planners) and represents these accurately. Workshops may provide the best route to interact with key experts on the model development.

5.6.3. An integrated effort

The future scenarios presented in Chapter 4 provide the first level of granularity of development of the scenario descriptions. The next iteration of future scenario development will add detail to these future scenarios. The final future scenarios will provide rich individual stories using quantitative results from the business environment modelling and narrative descriptions from the VIBES software and factors mapping feedback. The modelling and interactions with the key experts using the VIBES tool and factors maps could provide an integrated effort to developing the future scenarios descriptions.

5.6.4. Business environment modelling within VIVACE

The business environment modelling work has adopted a high level of analysis. This means analysing the extended value chain on a conceptual level that includes environmental and competitive elements in addition to extended value chain organisations. This high level approach may be used to formulate business strategy and value chain strategy. The work is needed to investigate how the sustainability of the extended value chain in Europe can be improved while considering the environmental factors that are likely to compromise its performance.




Many of work packages within the VIVACE project are designed to focus on operational level. An operational perspective is necessary for the development of specific tools and technologies. The higher system level of analysis described in this chapter complements the research in other work packages that are analysing systems at an operational level (such as WP2.5) because it provides the business environment context. However, the value of the higher systems analysis will only be realised if it is used to inform developments at an operational level. Chapter 6 continues this topic by describing value chain strategies in operational terms.




6. CHAPTER 6: FUTURE VALUE CHAIN DESCRIPTION

6.1. INTRODUCTION This chapter describes our initial work in describing value chains of the future. The approach we use provides a physical view of the constituent elements. This approach complements the business environment modelling work that provides conceptual models of the value chain strategy at a high systems level. The high level approach should be converted to practical value chain design at an operations level. For this we need to think about the value chain in terms of constituent elements. Firstly we present a popular view of value chain elements and then review this in the context of our future work in describing value chains for the aerospace industry.

6.2. DESCRIBING THE VALUE CHAIN Michael Porter (1985) described the Value Chain in the following way:

“The value chain categorizes the generic value-adding activities of an organization. The main activities are: outbound logistics, operation, inbound logistics, sales and marketing, services. These activities are supported by: administrative infrastructure management, human resources management, R&D, and procurement. The costs and value drivers are identified for each value activity. Its ultimate goal is to maximize value creation while minimizing costs.”

The concept has been extended beyond individual organizations. It can apply to whole supply chains and distribution networks. The delivery of a mix of products and services to the end customer will mobilize different economic actors, each managing its own value chain. The industry wide synchronized interactions of those local value chains create an extended value chain, sometimes global in extent. Capturing the value generated along the chain is the new approach taken by many management strategists. By exploiting the upstream and downstream information flowing along the value chain the firms may try to bypass the intermediaries creating new business models.

6.3. DEVELOPMENT OF VALUE CHAIN ANALYSIS WITHIN VIVACE The goal for the VIVACE work within subtask 2.1.1.3 is to map and understand the aviation value stream so it could be possible to create a new business model. In this work we will look at the value stream from the operator and down to the lowest supplier in the chain. The principal stages are shown in figure 6.1:




Figure 6.1: Principal stages of the value chain.

A typical value chain analysis can be performed in the following steps:

1. Analysis of own value chain – the costs that are related to every single activity. 2. Analysis of customers’ value chains – how does our product fit into their value chain? 3. Identification of potential cost advantages in comparison with competitors. 4. Identification of potential value added for the customer – how can our product add

value to the customers’ value chain (e.g. lower costs or higher performance) – where does the customer see such potential?

Porter describes the internal value chain, or internal value chain in an extended enterprise, as we have looked into earlier, as shown in figure 6.2. He distinguishes between primary activities and support activities. Primary activities are directly concerned with the creation or delivery of a product or service. They can be grouped into five main areas: inbound logistics, operations, outbound logistics, marketing and sales, and service. Each of these primary activities is linked to support activities that help to improve their effectiveness or efficiency. There are four main areas of support activities: procurement, technology development (including R&D), human resource management, and infrastructure (systems for planning, finance, quality, information management etc.).

Carlton

Volvo Aero

Rolls-Royce

Lufthansa

Airbus

1

5

4

3

2

Carlton

Volvo Aero

Rolls-Royce

Lufthansa

Airbus

1

5

4

3

2

Inbound LogisticsInbound Logistics

Operations

Outbound Logistics

Marketing and Sales

Services

Procurement

Technology Development

Human Resource Management

Infrastructure

SupportA

ctivities

Primary Activities

Mar

gin

Margin




Figure 6.2: The basic model of Porter’s Value Chain (source: Porter, 1985).

In most industries, it is unusual for a single company to perform all activities from product design, production of components, and final assembly to delivery to the final user by itself. Most often, organizations are elements of a value system or supply chain. Hence, value chain analysis should cover the whole value system in which the organization operates, as shown in figure 6.3.

Figure 6.3: Porter’s whole value chain (source: Porter, 1985).

And in the extended enterprise that we are working, we need to follow the second approach. In the first part of this work focus will be on stage 1 and 2 in the list, analysing the total value of the value stream and how this value stream is shared downstream. That means that we want to answer the following questions.

• How big is the market (civil and freight)? • What kinds of players do we find in the market? • How does the top level distribute the money to the next level? • What kinds of hardware and software do we find in the value chain? • What kinds of relationships do we find in the value chain?

In this part of the work we will look at the value stream, how the money, hardware and software are distributed in the aviation industry, to develop our knowledge of the industry. We will follow the main value streams in the industry in more detail as shown in figure 6.4:

SupplierValue Chains

CustomerValue Chains

ChannelValue Chains

Organisation’sValue Chains




Figure 6.4: Detailed model of the value chain

A significant analysis has already been done in this area. We know that the total revenue in the industry today is around $330 Billion (Air Transport Association 2004b). This is the same as the revenue stream to the operator on level 1. We have also done some studies on level 1 that are summarised in figure 6.5:

Figure 6.5: Operator expenses.

Insurance Fuel Aircraft/Engine Maintenance Labor Catering

Operator

Structures ”Systems” InteriorLandinggear

Compressor Burning Turbine ”systems”Fan modul

Engines

LPT Blades Discs ”Systems”

Landingfee

Forging Logistic

NON-AIRCRAFT INSURANCE

1%

PASSENGER COMMISSIONS

2%

AIRCRAFT INSURANCE0%

MAINTENANCE MATERIAL

2%

LANDING FEES2%

FOOD & BEVERAGE2%

PROFESSIONAL SERVICES

8%

COMMUNICATION1%

UTILITIES & OFFICE SUPPLIES

1%

ADVERSTISING & PROMOTION

1%

NON-AIRCRAFT OWNERSHIP

5%

AIRCRAFT OWNERSHIP10%

FUEL15%

LABOR31%

OTHER OP. EXPENSES19%




Here we can find the main cost for an operator, who is the same as the revenue stream further down in the chain. We will not in this paper describe this work in detail because the delivery of this work is timetabled for 2005.

6.4. CONCLUSIONS ON FURTHER WORK In the next step of the work we will focus on stage 3 and 4 in the list by analysing the value chain. And now the focus changes from not only financial aspects but to what is adding value in the industry. It is here that most of the work in this sub task will be done. It is here we will try to explore different ways of adding value in the value chain, and maybe more importantly, explore new ways of building the value chain, so that the customer (passenger) will get more value for less cost.




7. CHAPTER 7: CONCLUSIONS

7.1. INTRODUCTION

This chapter completes the report, offering an overview of the work detailed in the preceding chapters and presenting final conclusions. The work to be conducted in the months to come is discussed, and some longer-term opportunities for further work are proposed.

7.2. SUMMARY OF BUSINESS ENVIRONMENT DEFINITION ACTIVITIES

The work conducted to-date can be identified as belonging to three distinct areas:

• Identification of drivers and factors affecting the air transportation industry.

• Formulation of initial business environment scenarios.

• Scoping and structuring of models to investigate the dynamic behaviour of key aspects of the aerospace business environment.

Beginning with an overview of business environment modelling methods (see Chapter 2), this document shows how those methods were employed to provide a detailed description of the context in which aerospace business is conducted.

To facilitate this, an extensive literature review was carried out, starting with the publications from ACARE that are identified in the VIVACE Description of Work as being of particular value. (Appendix 1 provides a review of the ACARE work; the authors feel this will be useful in presenting the findings of ACARE to the wider VIVACE community.)

Reviews of other literature, plus interviews with industrial partners have resulted in the creation of a multi-level factors map showing the complex interrelationships in the aerospace business environment. This can be seen in Chapter 3. The factors that appear to be most important are: costs, security, environment, and regulation. Changes in these factors are expected to have a significant impact on the future of the aerospace industry. Initial feedback from the industry suggests that, with minor changes, the factors map provides a comprehensive list of the factors influencing the aerospace industry.

The level of understanding achieved with respect to key industry factors has facilitated the creation of a set of initial business environment scenarios. These offer those involved with air transportation in any capacity (airframe and engine manufacturers, operators, legislators, etc.) an opportunity to explore a wide variety of possible futures. In total, nineteen key variables have been identified, with the extent of each described by a pair of scenarios. These can now be used to provoke strategic thought among stakeholders, and to generate




descriptions of possible futures that are of interest because they present opportunities or threats.

An initial prototype software tool called VIBES (VIVACE Interactive Business Environment Simulator) was created to encourage industry experts to experiment with the impact of future business environments, and to gather feedback on the themes that were most often of interest, since these are likely to be prime candidates for further investigation via modelling.

The report has provided an introduction to concepts in scenario analysis and modelling. System dynamics is being proposed as the approach for modelling the dynamic behaviour of the aerospace market, and previous system dynamics studies of relevance to VIVACE were reviewed. An initial model of the VIVACE business environment sub-systems has been presented, to be used as the basis for developing a decision support model for commercial planners for the evaluation of strategies.

The work in describing value chains provides ‘a bottom up’ approach to developing value chain strategies for the future. The approach in modelling the business environment which takes a high systems level provides a top down perspective on value chain development. These approaches will complement each other in developing innovative but practical value chain strategies for the aerospace industry of the future.

Figure 7.1: Perspectives on the value chain (see Figures 5.4 and 6.4 for detail)

Research activities conducted during the first stage of task 2.1.1 are summarised in figure 7.2. More detailed contributions, plus future work for each activity, are summarised in figure 7.3.




Literature review

Development offactors map listing31 factors

Identification of key factorsin terms of importance anduncertainties

Development of 19 pairs ofinitial scenarios

Combination of scenariosinto themes

ACARE Literature Industry input

AircraftfleetAircraft

fleet

Demand fornew aircraftDemand for

new aircraft

Global trade

Business cyclePassenger

attitude

Security

GDP

Taxation

Subsidy

OperatorRevenueOperator

RevenueYield(Price x RPK)Yield

(Price x RPK)



EnvironmentGreen

technology

OperatingCostsOperating

Costs

Airportcapacity

RegulationSafety

Exchange rateCost of

financialservices

Cost offuel

Demographics

Certification

AircraftretirementAircraft

retirement

Demand formaintenanceDemand for

maintenanceAir traffic

management

Price ofticketPrice of

ticket

No ofPassengersNo of

Passengers DistanceDistance

Passenger Traffic

No.ofFreight (ton)No.of

Freight (ton)

Freight Traffic

Politics

Politicalfactors

Economicfactors

Technologyfactors

Socialfactors

Influence

Macro-environment factors

IndustryfactorsIndustry

factors

Cost ofmaintenanceCost of

maintenance

1. Hub airportsor direct flights

1. Hub airportsor direct flights 2. Aircraft age2. Aircraft age 3. Partnerships

on routes3. Partnerships

on routes4. Airportavailability4. Airportavailability

5. Quality ofservice

5. Quality ofservice

6. Journeylength

6. Journeylength 7. Conflict7. Conflict 8. Fuel

availability8. Fuel

availability

9. Spare partsmanufacture

9. Spare partsmanufacture

10. East andWest

10. East andWest

11. Environmentalissues

11. Environmentalissues

12. Spaceactivity

12. Spaceactivity

13. Operatorvs. manufacturer

13. Operatorvs. manufacturer

14. Privateaviation

14. Privateaviation

15. Attitudesto risk

15. Attitudesto risk

16. Size ofpayload

16. Size ofpayload

17. Productvariety

17. Productvariety

18. Businessstart-ups

18. Businessstart-ups

19. Freightactivity

19. Freightactivity n. Others?n. Others?

Demand (mostly ‘the passenger’but includes freight)

Demand (mostly ‘the passenger’but includes freight)

LegislatorsLegislators

OperatorsOperators

ManufacturersManufacturers

Politics andeconomics

Politics andeconomics

Modelling key scenarios

Literature onscenario analysis

Literature onmodelling

Figure 7.2: Research activities (see Figures 3.1 and 4.2 for detail)




Figure 7.3: Summary of contributions to-date and future work

7.3. FURTHER WORK

Work is now underway to circulate the factors map among industry experts, and further work will be carried out to further enhance the factors map in response to comments received. Some factors may well be amalgamated to simplify the map, and focus on the most important relationships and key factors.

Another main task in the next stage of the research is the work on interface and value chain analysis research. Initial investigation has been conducted to gain insights into the state-of-the-art in value chain research and practice.

With regard to business scenarios, although the work conducted to-date allows a wide range of initial business environments to be represented, the response scenarios selected by the industry need to be investigates, describing how the aerospace value chain might change in response to the challenges posed by the future business environment.

Specifically we are intending to develop the Visual Interactive Business Environment System (VIBES) concepts and the software. A prototype demonstration package is expected in M18. This will be informed through a workshop with relevant industry personnel. We will produce a state-of the art review of Value Chain modelling techniques of specific relevance to the aerospace sector by M24. By M30 we will produce an updated report on the Future Business Environment that will contain business environment simulation models and a selected approach for value chain mapping.




The system dynamics modelling of the business environment, as described in Chapter 5, can provide an analysis of market behaviour, and may be of value within other VIVACE work packages, including:

• Task 2.1.3 - The 7 day Virtual Enterprise

• WP 2.5 – Supply Chain Manufacturing Workflow Simulation

The work on business and value chain analysis and modelling is continuing to develop and test scenario models to capture, analyse and understand future business environments in the aerospace sector. This will require a number of iterations for information refinement and validation from the industry and will involve our partners in the work package. The ultimate goal is to develop simulation models and provide examples to explore how extended enterprises can be formed and act in an aerospace business environment and to analyse their value chains.

We appreciate feedback on any aspects of the Business Environment, scenario analysis and modelling or value chain work.




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Glossary of Terms ACARE: Advisory Council for Aeronautics Research in Europe ATA: Air Transport Association ATM: Air Traffic Management Business environment: The market and factors driving the market characteristics. Business environment modelling: A method of representing the market and describing how the characteristics of the market change over time. EMF: European Metalworkers’ Federation Factor: Issues and forces that act upon the subject (in this case, the aerospace industry). Factors maps: Illustrations that depict the factors influencing the subject (or an element being studied in detail), showing the dependencies and relationships between the factors. IATA: International Air Transport Association ICAO: International Civil Aviation Organisation Industry metrics: Common measures used within the aerospace industry, and by staff on WP2.1.1, to study the economics of air travel. Examples include freight tonnage per year, mean journey length, and percentage of seats occupied. (Section 4.5 includes a list of some of the metrics that have been used in models to date.) MRO: Maintenance, Repair and Overhaul Scenario: A description of possible outcomes in a given situation. Hypothetical situations are described, based upon the extrapolation of trends, describing how a situation might come about. Such scenarios are used to promote understanding of the options available, rather than to predicting specific outcomes. System Dynamics: An approach to modelling the dynamic behaviour of markets and the development of policies to control aspects of the markets. Theme: While scenarios typically deal with a narrow subset of issues, a theme may be created from a set of future scenarios that compliment each other, describing a future environment in more detail.

Value chain: The process steps and business activities required to transform raw materials and knowledge into a customer offering.

PRELIMINARY DESCRIPTION OF THE FUTURE AEROSPACE … · 2.3.1. Initial Scenario Formulation ......

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